-module(autonomous_goal_planner). -behaviour(gen_server). %% Autonomous Goal Formation and Planning Engine %% Sophisticated system for autonomous goal formation and planning that enables agents to: %% - Autonomously form goals based on needs, drives, and environmental opportunities %% - Create hierarchical goal structures with sub-goals and dependencies %% - Plan sequences of actions to achieve goals %% - Dynamically adjust goals and plans based on changing circumstances %% - Balance multiple competing goals and resource constraints %% - Learn from goal pursuit outcomes to improve future planning %% - Form meta-goals about the goal formation process itself -export([start_link/1, % Core goal formation form_autonomous_goals/2, update_goal_hierarchy/2, prioritize_goals/2, decompose_complex_goal/2, identify_goal_conflicts/1, resolve_goal_conflicts/2, % Planning and execution create_action_plan/3, execute_plan/2, monitor_plan_execution/2, adapt_plan_during_execution/3, evaluate_plan_success/3, % Goal management activate_goal/2, deactivate_goal/2, suspend_goal/2, resume_goal/2, merge_compatible_goals/2, split_complex_goal/2, % Resource and constraint handling analyze_resource_requirements/2, check_resource_availability/2, optimize_resource_allocation/2, handle_resource_conflicts/2, % Learning and adaptation learn_from_goal_outcomes/3, adapt_goal_formation_strategies/2, update_goal_preferences/3, evolve_goal_structures/2, % Meta-goal processing form_meta_goals/2, reason_about_goal_formation/2, optimize_goal_formation_process/1, evaluate_goal_formation_effectiveness/1]). -export([init/1, handle_call/3, handle_cast/2, handle_info/2, terminate/2, code_change/3]). %% Goal and planning data structures -record(autonomous_goal, { goal_id, % Unique goal identifier goal_type, % Type of goal (survival, exploration, achievement, etc.) goal_description, % Human-readable goal description goal_parameters = #{}, % Parameters defining the goal priority = 0.5, % Goal priority (0-1) urgency = 0.5, % Goal urgency (0-1) importance = 0.5, % Goal importance (0-1) difficulty = 0.5, % Estimated difficulty (0-1) resource_requirements = #{}, % Required resources preconditions = [], % Conditions that must be met success_criteria = [], % Criteria for goal success failure_criteria = [], % Criteria indicating goal failure time_constraints = #{}, % Time-related constraints dependencies = [], % Dependencies on other goals sub_goals = [], % Sub-goals for goal decomposition parent_goal = undefined, % Parent goal (if this is a sub-goal) status = inactive, % Current status (inactive, active, suspended, completed, failed) progress = 0.0, % Progress towards completion (0-1) creation_time, % When goal was created activation_time = undefined, % When goal was activated completion_time = undefined, % When goal was completed motivation_source, % What motivated this goal learning_value = 0.5, % Value for learning from this goal adaptation_history = [] % History of adaptations to this goal }). -record(action_plan, { plan_id, % Unique plan identifier goal_id, % Goal this plan serves plan_type, % Type of planning (sequential, parallel, conditional, etc.) actions = [], % Sequence of actions execution_strategy, % How to execute the plan resource_allocation = #{}, % Resource allocation for plan time_estimate, % Estimated time to complete success_probability = 0.5, % Estimated probability of success risk_assessment = #{}, % Risk analysis contingency_plans = [], % Alternative plans if main plan fails monitoring_checkpoints = [], % Checkpoints for monitoring progress adaptation_triggers = [], % Conditions that trigger plan adaptation execution_status = not_started, % Current execution status execution_progress = 0.0, % Progress in plan execution (0-1) execution_history = [], % History of plan execution performance_metrics = #{}, % Performance metrics for the plan lessons_learned = [] % Lessons learned from plan execution }). -record(planning_state, { agent_id, % Associated agent active_goals = #{}, % Currently active goals goal_hierarchy = [], % Hierarchical structure of goals goal_formation_strategies = [], % Strategies for forming goals planning_algorithms = [], % Available planning algorithms execution_monitors = #{}, % Monitors for plan execution resource_state = #{}, % Current resource availability goal_preferences = #{}, % Learned preferences about goals performance_history = [], % History of goal/plan performance meta_goals = [], % Meta-goals about goal formation conflict_resolution_strategies = [], % Strategies for resolving goal conflicts learning_parameters = #{}, % Parameters for learning from outcomes environmental_opportunities = [], % Current environmental opportunities internal_drives = #{} % Internal drives and motivations }). %%==================================================================== %% API functions %%==================================================================== start_link(Config) -> AgentId = maps:get(agent_id, Config, generate_planner_id()), io:format("[GOAL_PLANNER] Starting autonomous goal planner for agent ~p~n", [AgentId]), gen_server:start_link(?MODULE, [AgentId, Config], []). %% Core goal formation form_autonomous_goals(PlannerPid, Context) -> gen_server:call(PlannerPid, {form_autonomous_goals, Context}). update_goal_hierarchy(PlannerPid, Updates) -> gen_server:call(PlannerPid, {update_goal_hierarchy, Updates}). prioritize_goals(PlannerPid, PrioritizationContext) -> gen_server:call(PlannerPid, {prioritize_goals, PrioritizationContext}). decompose_complex_goal(PlannerPid, ComplexGoal) -> gen_server:call(PlannerPid, {decompose_complex_goal, ComplexGoal}). identify_goal_conflicts(PlannerPid) -> gen_server:call(PlannerPid, identify_goal_conflicts). resolve_goal_conflicts(PlannerPid, ConflictResolutionStrategy) -> gen_server:call(PlannerPid, {resolve_goal_conflicts, ConflictResolutionStrategy}). %% Planning and execution create_action_plan(PlannerPid, GoalId, PlanningContext) -> gen_server:call(PlannerPid, {create_action_plan, GoalId, PlanningContext}). execute_plan(PlannerPid, PlanId) -> gen_server:call(PlannerPid, {execute_plan, PlanId}). monitor_plan_execution(PlannerPid, PlanId) -> gen_server:call(PlannerPid, {monitor_plan_execution, PlanId}). adapt_plan_during_execution(PlannerPid, PlanId, AdaptationTrigger) -> gen_server:call(PlannerPid, {adapt_plan_during_execution, PlanId, AdaptationTrigger}). evaluate_plan_success(PlannerPid, PlanId, OutcomeData) -> gen_server:call(PlannerPid, {evaluate_plan_success, PlanId, OutcomeData}). %% Goal management activate_goal(PlannerPid, GoalId) -> gen_server:call(PlannerPid, {activate_goal, GoalId}). deactivate_goal(PlannerPid, GoalId) -> gen_server:call(PlannerPid, {deactivate_goal, GoalId}). suspend_goal(PlannerPid, GoalId) -> gen_server:call(PlannerPid, {suspend_goal, GoalId}). resume_goal(PlannerPid, GoalId) -> gen_server:call(PlannerPid, {resume_goal, GoalId}). merge_compatible_goals(PlannerPid, GoalIds) -> gen_server:call(PlannerPid, {merge_compatible_goals, GoalIds}). split_complex_goal(PlannerPid, GoalId) -> gen_server:call(PlannerPid, {split_complex_goal, GoalId}). %% Resource and constraint handling analyze_resource_requirements(PlannerPid, GoalId) -> gen_server:call(PlannerPid, {analyze_resource_requirements, GoalId}). check_resource_availability(PlannerPid, ResourceRequirements) -> gen_server:call(PlannerPid, {check_resource_availability, ResourceRequirements}). optimize_resource_allocation(PlannerPid, Goals) -> gen_server:call(PlannerPid, {optimize_resource_allocation, Goals}). handle_resource_conflicts(PlannerPid, ConflictingGoals) -> gen_server:call(PlannerPid, {handle_resource_conflicts, ConflictingGoals}). %% Learning and adaptation learn_from_goal_outcomes(PlannerPid, GoalId, Outcome) -> gen_server:cast(PlannerPid, {learn_from_goal_outcomes, GoalId, Outcome}). adapt_goal_formation_strategies(PlannerPid, PerformanceData) -> gen_server:cast(PlannerPid, {adapt_goal_formation_strategies, PerformanceData}). update_goal_preferences(PlannerPid, GoalType, PreferenceUpdate) -> gen_server:cast(PlannerPid, {update_goal_preferences, GoalType, PreferenceUpdate}). evolve_goal_structures(PlannerPid, EvolutionPressure) -> gen_server:cast(PlannerPid, {evolve_goal_structures, EvolutionPressure}). %% Meta-goal processing form_meta_goals(PlannerPid, MetaContext) -> gen_server:call(PlannerPid, {form_meta_goals, MetaContext}). reason_about_goal_formation(PlannerPid, ReasoningContext) -> gen_server:call(PlannerPid, {reason_about_goal_formation, ReasoningContext}). optimize_goal_formation_process(PlannerPid) -> gen_server:call(PlannerPid, optimize_goal_formation_process). evaluate_goal_formation_effectiveness(PlannerPid) -> gen_server:call(PlannerPid, evaluate_goal_formation_effectiveness). %%==================================================================== %% gen_server callbacks %%==================================================================== init([AgentId, Config]) -> process_flag(trap_exit, true), io:format("[GOAL_PLANNER] Initializing autonomous goal planner for agent ~p~n", [AgentId]), % Initialize goal formation strategies GoalFormationStrategies = initialize_goal_formation_strategies(Config), % Initialize planning algorithms PlanningAlgorithms = initialize_planning_algorithms(Config), % Initialize internal drives InternalDrives = initialize_internal_drives(Config), % Initialize learning parameters LearningParams = initialize_learning_parameters(Config), State = #planning_state{ agent_id = AgentId, goal_formation_strategies = GoalFormationStrategies, planning_algorithms = PlanningAlgorithms, internal_drives = InternalDrives, learning_parameters = LearningParams }, % Start goal formation and planning cycles schedule_goal_formation_cycle(), schedule_plan_monitoring_cycle(), schedule_resource_monitoring_cycle(), {ok, State}. handle_call({form_autonomous_goals, Context}, _From, State) -> io:format("[GOAL_PLANNER] Forming autonomous goals for context: ~p~n", [Context]), % Analyze current situation and needs SituationAnalysis = analyze_current_situation(Context, State), % Identify potential goals based on multiple sources PotentialGoals = identify_potential_goals(SituationAnalysis, State), % Evaluate and filter goals EvaluatedGoals = evaluate_potential_goals(PotentialGoals, State), % Select goals to pursue SelectedGoals = select_goals_for_pursuit(EvaluatedGoals, State), % Create goal structures CreatedGoals = create_goal_structures(SelectedGoals, State), % Update goal hierarchy NewGoalHierarchy = update_hierarchy_with_new_goals(CreatedGoals, State#planning_state.goal_hierarchy), % Update active goals NewActiveGoals = activate_selected_goals(CreatedGoals, State#planning_state.active_goals), NewState = State#planning_state{ goal_hierarchy = NewGoalHierarchy, active_goals = NewActiveGoals }, {reply, {ok, CreatedGoals}, NewState}; handle_call({decompose_complex_goal, ComplexGoal}, _From, State) -> io:format("[GOAL_PLANNER] Decomposing complex goal: ~p~n", [ComplexGoal#autonomous_goal.goal_id]), % Analyze goal complexity ComplexityAnalysis = analyze_goal_complexity(ComplexGoal), % Apply decomposition strategies DecompositionStrategy = select_decomposition_strategy(ComplexityAnalysis, State), SubGoals = apply_decomposition_strategy(ComplexGoal, DecompositionStrategy, State), % Establish sub-goal relationships SubGoalRelationships = establish_subgoal_relationships(SubGoals, ComplexGoal), % Update goal hierarchy UpdatedHierarchy = insert_subgoals_in_hierarchy(SubGoals, SubGoalRelationships, State#planning_state.goal_hierarchy), NewState = State#planning_state{goal_hierarchy = UpdatedHierarchy}, {reply, {ok, SubGoals}, NewState}; handle_call({create_action_plan, GoalId, PlanningContext}, _From, State) -> io:format("[GOAL_PLANNER] Creating action plan for goal: ~p~n", [GoalId]), % Get goal details case maps:find(GoalId, State#planning_state.active_goals) of {ok, Goal} -> % Analyze planning requirements PlanningRequirements = analyze_planning_requirements(Goal, PlanningContext, State), % Select planning algorithm PlanningAlgorithm = select_planning_algorithm(PlanningRequirements, State), % Generate action plan ActionPlan = generate_action_plan(Goal, PlanningAlgorithm, PlanningContext, State), % Validate and optimize plan OptimizedPlan = validate_and_optimize_plan(ActionPlan, State), % Store plan PlanId = OptimizedPlan#action_plan.plan_id, {reply, {ok, PlanId, OptimizedPlan}, State}; error -> {reply, {error, goal_not_found}, State} end; handle_call({execute_plan, PlanId}, _From, State) -> io:format("[GOAL_PLANNER] Executing plan: ~p~n", [PlanId]), % Start plan execution ExecutionResult = start_plan_execution(PlanId, State), % Set up execution monitoring setup_execution_monitoring(PlanId, State), {reply, {ok, ExecutionResult}, State}; handle_call(identify_goal_conflicts, _From, State) -> io:format("[GOAL_PLANNER] Identifying goal conflicts~n"), % Analyze conflicts between active goals ActiveGoals = maps:values(State#planning_state.active_goals), % Find resource conflicts ResourceConflicts = find_resource_conflicts(ActiveGoals), % Find logical conflicts LogicalConflicts = find_logical_conflicts(ActiveGoals), % Find temporal conflicts TemporalConflicts = find_temporal_conflicts(ActiveGoals), AllConflicts = #{ resource_conflicts => ResourceConflicts, logical_conflicts => LogicalConflicts, temporal_conflicts => TemporalConflicts }, {reply, {ok, AllConflicts}, State}; handle_call({resolve_goal_conflicts, ConflictResolutionStrategy}, _From, State) -> io:format("[GOAL_PLANNER] Resolving goal conflicts with strategy: ~p~n", [ConflictResolutionStrategy]), % Identify current conflicts Conflicts = identify_all_conflicts(State), % Apply conflict resolution strategy ResolutionResults = apply_conflict_resolution(Conflicts, ConflictResolutionStrategy, State), % Update goals based on resolution UpdatedGoals = update_goals_from_resolution(ResolutionResults, State#planning_state.active_goals), % Update goal hierarchy UpdatedHierarchy = update_hierarchy_from_resolution(ResolutionResults, State#planning_state.goal_hierarchy), NewState = State#planning_state{ active_goals = UpdatedGoals, goal_hierarchy = UpdatedHierarchy }, {reply, {ok, ResolutionResults}, NewState}; handle_call({prioritize_goals, PrioritizationContext}, _From, State) -> io:format("[GOAL_PLANNER] Prioritizing goals~n"), % Get all active goals ActiveGoals = maps:values(State#planning_state.active_goals), % Apply prioritization algorithm PrioritizationResult = prioritize_goals_internal(ActiveGoals, PrioritizationContext, State), % Update goal priorities UpdatedGoals = update_goal_priorities(PrioritizationResult, State#planning_state.active_goals), NewState = State#planning_state{active_goals = UpdatedGoals}, {reply, {ok, PrioritizationResult}, NewState}; handle_call({form_meta_goals, MetaContext}, _From, State) -> io:format("[GOAL_PLANNER] Forming meta-goals~n"), % Analyze current goal formation process GoalFormationAnalysis = analyze_goal_formation_process(State), % Identify areas for improvement ImprovementAreas = identify_improvement_areas(GoalFormationAnalysis, State), % Generate meta-goals MetaGoals = generate_meta_goals(ImprovementAreas, MetaContext, State), % Add meta-goals to state UpdatedMetaGoals = MetaGoals ++ State#planning_state.meta_goals, NewState = State#planning_state{meta_goals = UpdatedMetaGoals}, {reply, {ok, MetaGoals}, NewState}; handle_call(optimize_goal_formation_process, _From, State) -> io:format("[GOAL_PLANNER] Optimizing goal formation process~n"), % Analyze current process effectiveness ProcessAnalysis = analyze_process_effectiveness(State), % Identify optimization opportunities OptimizationOpportunities = identify_process_optimizations(ProcessAnalysis, State), % Apply optimizations OptimizedStrategies = apply_process_optimizations(OptimizationOpportunities, State#planning_state.goal_formation_strategies), NewState = State#planning_state{goal_formation_strategies = OptimizedStrategies}, {reply, {ok, OptimizationOpportunities}, NewState}; handle_call(_Request, _From, State) -> {reply, {error, unknown_request}, State}. handle_cast({learn_from_goal_outcomes, GoalId, Outcome}, State) -> io:format("[GOAL_PLANNER] Learning from goal outcome: ~p -> ~p~n", [GoalId, Outcome]), % Extract lessons from outcome Lessons = extract_lessons_from_outcome(GoalId, Outcome, State), % Update goal preferences UpdatedPreferences = update_preferences_from_lessons(Lessons, State#planning_state.goal_preferences), % Update goal formation strategies UpdatedStrategies = update_strategies_from_lessons(Lessons, State#planning_state.goal_formation_strategies), % Record performance history PerformanceRecord = create_performance_record(GoalId, Outcome, Lessons), UpdatedHistory = [PerformanceRecord | State#planning_state.performance_history], NewState = State#planning_state{ goal_preferences = UpdatedPreferences, goal_formation_strategies = UpdatedStrategies, performance_history = UpdatedHistory }, {noreply, NewState}; handle_cast({adapt_goal_formation_strategies, PerformanceData}, State) -> io:format("[GOAL_PLANNER] Adapting goal formation strategies~n"), % Analyze performance data PerformanceAnalysis = analyze_performance_data(PerformanceData, State), % Identify strategy adaptations StrategyAdaptations = identify_strategy_adaptations(PerformanceAnalysis, State), % Apply adaptations AdaptedStrategies = apply_strategy_adaptations(StrategyAdaptations, State#planning_state.goal_formation_strategies), NewState = State#planning_state{goal_formation_strategies = AdaptedStrategies}, {noreply, NewState}; handle_cast(_Msg, State) -> {noreply, State}. handle_info(goal_formation_cycle, State) -> % Periodic autonomous goal formation NewState = perform_autonomous_goal_formation_cycle(State), schedule_goal_formation_cycle(), {noreply, NewState}; handle_info(plan_monitoring_cycle, State) -> % Periodic plan monitoring and adaptation NewState = perform_plan_monitoring_cycle(State), schedule_plan_monitoring_cycle(), {noreply, NewState}; handle_info(resource_monitoring_cycle, State) -> % Periodic resource monitoring NewState = perform_resource_monitoring_cycle(State), schedule_resource_monitoring_cycle(), {noreply, NewState}; handle_info(_Info, State) -> {noreply, State}. terminate(_Reason, State) -> io:format("[GOAL_PLANNER] Autonomous goal planner for agent ~p terminating~n", [State#planning_state.agent_id]), save_planning_state(State), ok. code_change(_OldVsn, State, _Extra) -> {ok, State}. %%==================================================================== %% Internal functions - Goal Formation %%==================================================================== analyze_current_situation(Context, State) -> % Analyze current situation to identify goal formation opportunities % Environmental analysis EnvironmentalFactors = analyze_environmental_factors(Context, State), % Internal state analysis InternalFactors = analyze_internal_factors(State), % Resource analysis ResourceFactors = analyze_resource_factors(State), % Opportunity analysis Opportunities = identify_opportunities(Context, State), % Threat analysis Threats = identify_threats(Context, State), #{ environmental_factors => EnvironmentalFactors, internal_factors => InternalFactors, resource_factors => ResourceFactors, opportunities => Opportunities, threats => Threats, analysis_timestamp => erlang:system_time(second) }. identify_potential_goals(SituationAnalysis, State) -> % Identify potential goals from multiple sources % Need-driven goals NeedDrivenGoals = identify_need_driven_goals(SituationAnalysis, State), % Opportunity-driven goals OpportunityDrivenGoals = identify_opportunity_driven_goals(SituationAnalysis, State), % Curiosity-driven goals CuriosityDrivenGoals = identify_curiosity_driven_goals(SituationAnalysis, State), % Achievement-driven goals AchievementDrivenGoals = identify_achievement_driven_goals(SituationAnalysis, State), % Meta-cognitive goals MetaCognitiveGoals = identify_meta_cognitive_goals(SituationAnalysis, State), % Combine all potential goals AllPotentialGoals = NeedDrivenGoals ++ OpportunityDrivenGoals ++ CuriosityDrivenGoals ++ AchievementDrivenGoals ++ MetaCognitiveGoals, AllPotentialGoals. evaluate_potential_goals(PotentialGoals, State) -> % Evaluate potential goals based on multiple criteria lists:map(fun(Goal) -> % Evaluate goal value Value = evaluate_goal_value(Goal, State), % Evaluate goal feasibility Feasibility = evaluate_goal_feasibility(Goal, State), % Evaluate goal alignment with agent values Alignment = evaluate_goal_alignment(Goal, State), % Evaluate resource requirements ResourceScore = evaluate_resource_requirements(Goal, State), % Calculate overall score OverallScore = calculate_goal_score(Value, Feasibility, Alignment, ResourceScore), Goal#autonomous_goal{ importance = Value, difficulty = 1.0 - Feasibility, priority = OverallScore } end, PotentialGoals). select_goals_for_pursuit(EvaluatedGoals, State) -> % Select which goals to actually pursue % Sort by priority SortedGoals = lists:sort(fun(G1, G2) -> G1#autonomous_goal.priority >= G2#autonomous_goal.priority end, EvaluatedGoals), % Apply selection constraints MaxActiveGoals = get_max_active_goals(State), ResourceConstraints = get_resource_constraints(State), % Select goals within constraints SelectedGoals = select_goals_within_constraints(SortedGoals, MaxActiveGoals, ResourceConstraints, State), SelectedGoals. create_goal_structures(SelectedGoals, State) -> % Create full goal structures with all necessary information lists:map(fun(Goal) -> % Generate unique goal ID GoalId = generate_goal_id(), % Set creation time CreationTime = erlang:system_time(second), % Determine motivation source MotivationSource = determine_motivation_source(Goal, State), % Set initial status Status = determine_initial_status(Goal, State), Goal#autonomous_goal{ goal_id = GoalId, creation_time = CreationTime, motivation_source = MotivationSource, status = Status } end, SelectedGoals). %%==================================================================== %% Internal functions - Goal Decomposition %%==================================================================== analyze_goal_complexity(Goal) -> % Analyze how complex a goal is and how it should be decomposed % Analyze goal parameters ParameterComplexity = analyze_parameter_complexity(Goal#autonomous_goal.goal_parameters), % Analyze resource requirements ResourceComplexity = analyze_resource_complexity(Goal#autonomous_goal.resource_requirements), % Analyze success criteria CriteriaComplexity = analyze_criteria_complexity(Goal#autonomous_goal.success_criteria), % Analyze time constraints TemporalComplexity = analyze_temporal_complexity(Goal#autonomous_goal.time_constraints), #{ parameter_complexity => ParameterComplexity, resource_complexity => ResourceComplexity, criteria_complexity => CriteriaComplexity, temporal_complexity => TemporalComplexity, overall_complexity => (ParameterComplexity + ResourceComplexity + CriteriaComplexity + TemporalComplexity) / 4 }. select_decomposition_strategy(ComplexityAnalysis, State) -> % Select appropriate decomposition strategy based on complexity analysis OverallComplexity = maps:get(overall_complexity, ComplexityAnalysis), _AvailableStrategies = get_decomposition_strategies(State), % Select strategy based on complexity level if OverallComplexity > 0.8 -> hierarchical_decomposition; OverallComplexity > 0.6 -> temporal_decomposition; OverallComplexity > 0.4 -> functional_decomposition; true -> simple_decomposition end. apply_decomposition_strategy(Goal, Strategy, State) -> % Apply the selected decomposition strategy case Strategy of hierarchical_decomposition -> apply_hierarchical_decomposition(Goal, State); temporal_decomposition -> apply_temporal_decomposition(Goal, State); functional_decomposition -> apply_functional_decomposition(Goal, State); simple_decomposition -> apply_simple_decomposition(Goal, State); _ -> apply_general_decomposition(Goal, State) end. apply_hierarchical_decomposition(Goal, State) -> % Decompose goal into hierarchical sub-goals % Identify major components MajorComponents = identify_major_components(Goal, State), % Create sub-goals for each component SubGoals = lists:map(fun(Component) -> create_component_subgoal(Component, Goal, State) end, MajorComponents), % Establish hierarchy relationships establish_hierarchy_relationships(SubGoals, Goal), SubGoals. %%==================================================================== %% Internal functions - Planning %%==================================================================== analyze_planning_requirements(Goal, PlanningContext, State) -> % Analyze what kind of planning is needed for this goal % Analyze goal characteristics GoalCharacteristics = analyze_goal_characteristics(Goal), % Analyze environmental constraints EnvironmentalConstraints = analyze_environmental_constraints(PlanningContext), % Analyze resource constraints ResourceConstraints = analyze_resource_constraints(Goal, State), % Analyze temporal constraints TemporalConstraints = analyze_temporal_constraints(Goal, PlanningContext), #{ goal_characteristics => GoalCharacteristics, environmental_constraints => EnvironmentalConstraints, resource_constraints => ResourceConstraints, temporal_constraints => TemporalConstraints }. select_planning_algorithm(PlanningRequirements, State) -> % Select appropriate planning algorithm AvailableAlgorithms = State#planning_state.planning_algorithms, % Score algorithms for these requirements AlgorithmScores = score_planning_algorithms(PlanningRequirements, AvailableAlgorithms), % Select best algorithm BestAlgorithm = select_best_planning_algorithm(AlgorithmScores), BestAlgorithm. generate_action_plan(Goal, PlanningAlgorithm, PlanningContext, State) -> % Generate action plan using selected algorithm case PlanningAlgorithm of forward_chaining -> generate_forward_chaining_plan(Goal, PlanningContext, State); backward_chaining -> generate_backward_chaining_plan(Goal, PlanningContext, State); hierarchical_planning -> generate_hierarchical_plan(Goal, PlanningContext, State); reactive_planning -> generate_reactive_plan(Goal, PlanningContext, State); _ -> generate_general_plan(Goal, PlanningContext, State) end. %%==================================================================== %% Internal functions - Conflict Resolution %%==================================================================== find_resource_conflicts(Goals) -> % Find conflicts in resource requirements between goals % Collect all resource requirements AllResourceRequirements = collect_resource_requirements(Goals), % Identify overlapping requirements OverlappingRequirements = find_overlapping_requirements(AllResourceRequirements), % Identify conflicts where total requirements exceed availability ResourceConflicts = identify_resource_conflicts(OverlappingRequirements), ResourceConflicts. find_logical_conflicts(Goals) -> % Find logical conflicts between goals (mutually exclusive goals) % Analyze goal relationships GoalRelationships = analyze_goal_relationships(Goals), % Identify contradictory goals ContradictoryGoals = identify_contradictory_goals(GoalRelationships), % Identify mutually exclusive goals MutuallyExclusiveGoals = identify_mutually_exclusive_goals(GoalRelationships), #{ contradictory_goals => ContradictoryGoals, mutually_exclusive_goals => MutuallyExclusiveGoals }. find_temporal_conflicts(Goals) -> % Find temporal conflicts between goals % Analyze time constraints for all goals TimeConstraints = collect_time_constraints(Goals), % Identify overlapping time requirements TemporalOverlaps = find_temporal_overlaps(TimeConstraints), % Identify impossible temporal sequences ImpossibleSequences = find_impossible_sequences(TimeConstraints), #{ temporal_overlaps => TemporalOverlaps, impossible_sequences => ImpossibleSequences }. apply_conflict_resolution(Conflicts, Strategy, State) -> % Apply conflict resolution strategy case Strategy of priority_based -> apply_priority_based_resolution(Conflicts, State); resource_optimization -> apply_resource_optimization_resolution(Conflicts, State); temporal_scheduling -> apply_temporal_scheduling_resolution(Conflicts, State); goal_merging -> apply_goal_merging_resolution(Conflicts, State); goal_postponing -> apply_goal_postponing_resolution(Conflicts, State); _ -> apply_general_resolution(Conflicts, State) end. %%==================================================================== %% Internal functions - Cycles and Monitoring %%==================================================================== schedule_goal_formation_cycle() -> Interval = 60000, % 1 minute erlang:send_after(Interval, self(), goal_formation_cycle). schedule_plan_monitoring_cycle() -> Interval = 30000, % 30 seconds erlang:send_after(Interval, self(), plan_monitoring_cycle). schedule_resource_monitoring_cycle() -> Interval = 45000, % 45 seconds erlang:send_after(Interval, self(), resource_monitoring_cycle). perform_autonomous_goal_formation_cycle(State) -> % Perform periodic autonomous goal formation % Check if new goals should be formed ShouldFormNewGoals = should_form_new_goals(State), if ShouldFormNewGoals -> % Form new goals autonomously Context = create_autonomous_context(State), {ok, NewGoals} = form_autonomous_goals_internal(Context, State), integrate_new_goals(NewGoals, State); true -> State end. perform_plan_monitoring_cycle(State) -> % Monitor active plans and adapt as needed % Get all active plans ActivePlans = get_active_plans(State), % Monitor each plan MonitoringResults = lists:map(fun(Plan) -> monitor_plan_progress(Plan, State) end, ActivePlans), % Adapt plans that need adaptation AdaptedState = adapt_plans_based_on_monitoring(MonitoringResults, State), AdaptedState. perform_resource_monitoring_cycle(State) -> % Monitor resource availability and usage % Update resource state UpdatedResourceState = update_resource_state(State), % Check for resource conflicts ResourceConflicts = check_for_resource_conflicts(UpdatedResourceState, State), % Handle conflicts if any FinalState = handle_resource_conflicts_internal(ResourceConflicts, State#planning_state{resource_state = UpdatedResourceState}), FinalState. %%==================================================================== %% Internal functions - Utility and Helper Functions %%==================================================================== initialize_goal_formation_strategies(_Config) -> [ need_based_formation, opportunity_based_formation, curiosity_driven_formation, achievement_oriented_formation, meta_cognitive_formation ]. initialize_planning_algorithms(_Config) -> [ forward_chaining, backward_chaining, hierarchical_planning, reactive_planning, probabilistic_planning ]. initialize_internal_drives(_Config) -> #{ survival_drive => 0.8, exploration_drive => 0.6, achievement_drive => 0.5, social_drive => 0.4, creativity_drive => 0.3 }. initialize_learning_parameters(_Config) -> #{ learning_rate => 0.1, adaptation_rate => 0.05, preference_update_rate => 0.08, strategy_evolution_rate => 0.03 }. generate_planner_id() -> iolist_to_binary(io_lib:format("goal_planner_~p", [erlang:system_time(microsecond)])). generate_goal_id() -> iolist_to_binary(io_lib:format("goal_~p", [erlang:system_time(microsecond)])). save_planning_state(_State) -> % Save planning state to persistent storage ok. % Placeholder implementations for complex functions analyze_environmental_factors(_Context, _State) -> #{}. analyze_internal_factors(_State) -> #{}. analyze_resource_factors(_State) -> #{}. identify_opportunities(_Context, _State) -> []. identify_threats(_Context, _State) -> []. identify_need_driven_goals(_Analysis, _State) -> []. identify_opportunity_driven_goals(_Analysis, _State) -> []. identify_curiosity_driven_goals(_Analysis, _State) -> []. identify_achievement_driven_goals(_Analysis, _State) -> []. identify_meta_cognitive_goals(_Analysis, _State) -> []. evaluate_goal_value(_Goal, _State) -> 0.7. evaluate_goal_feasibility(_Goal, _State) -> 0.8. evaluate_goal_alignment(_Goal, _State) -> 0.6. evaluate_resource_requirements(_Goal, _State) -> 0.5. calculate_goal_score(Value, Feasibility, Alignment, Resource) -> (Value + Feasibility + Alignment + Resource) / 4. get_max_active_goals(_State) -> 5. get_resource_constraints(_State) -> #{}. select_goals_within_constraints(Goals, _Max, _Constraints, _State) -> lists:sublist(Goals, 3). determine_motivation_source(_Goal, _State) -> autonomous. determine_initial_status(_Goal, _State) -> inactive. update_hierarchy_with_new_goals(Goals, Hierarchy) -> Goals ++ Hierarchy. activate_selected_goals(Goals, ActiveGoals) -> lists:foldl(fun(Goal, Acc) -> maps:put(Goal#autonomous_goal.goal_id, Goal#autonomous_goal{status = active}, Acc) end, ActiveGoals, Goals). analyze_parameter_complexity(_Parameters) -> 0.5. analyze_resource_complexity(_Resources) -> 0.4. analyze_criteria_complexity(_Criteria) -> 0.6. analyze_temporal_complexity(_Constraints) -> 0.3. get_decomposition_strategies(_State) -> [hierarchical, temporal, functional, simple]. identify_major_components(_Goal, _State) -> [component1, component2]. create_component_subgoal(_Component, Goal, _State) -> Goal#autonomous_goal{goal_id = generate_goal_id()}. establish_hierarchy_relationships(_SubGoals, _Goal) -> ok. apply_temporal_decomposition(Goal, _State) -> [Goal]. apply_functional_decomposition(Goal, _State) -> [Goal]. apply_simple_decomposition(Goal, _State) -> [Goal]. apply_general_decomposition(Goal, _State) -> [Goal]. analyze_goal_characteristics(_Goal) -> #{}. analyze_environmental_constraints(_Context) -> #{}. analyze_resource_constraints(_Goal, _State) -> #{}. analyze_temporal_constraints(_Goal, _Context) -> #{}. score_planning_algorithms(_Requirements, Algorithms) -> [{A, 0.5} || A <- Algorithms]. select_best_planning_algorithm(Scores) -> element(1, hd(Scores)). generate_forward_chaining_plan(_Goal, _Context, _State) -> #action_plan{plan_id = generate_goal_id(), plan_type = forward_chaining}. generate_backward_chaining_plan(_Goal, _Context, _State) -> #action_plan{plan_id = generate_goal_id(), plan_type = backward_chaining}. generate_hierarchical_plan(_Goal, _Context, _State) -> #action_plan{plan_id = generate_goal_id(), plan_type = hierarchical}. generate_reactive_plan(_Goal, _Context, _State) -> #action_plan{plan_id = generate_goal_id(), plan_type = reactive}. generate_general_plan(_Goal, _Context, _State) -> #action_plan{plan_id = generate_goal_id(), plan_type = general}. validate_and_optimize_plan(Plan, _State) -> Plan. start_plan_execution(_PlanId, _State) -> #{status => started}. setup_execution_monitoring(_PlanId, _State) -> ok. collect_resource_requirements(Goals) -> [Goal#autonomous_goal.resource_requirements || Goal <- Goals]. find_overlapping_requirements(_Requirements) -> []. identify_resource_conflicts(_Overlapping) -> []. analyze_goal_relationships(_Goals) -> #{}. identify_contradictory_goals(_Relationships) -> []. identify_mutually_exclusive_goals(_Relationships) -> []. collect_time_constraints(Goals) -> [Goal#autonomous_goal.time_constraints || Goal <- Goals]. find_temporal_overlaps(_Constraints) -> []. find_impossible_sequences(_Constraints) -> []. identify_all_conflicts(_State) -> #{resource => [], logical => [], temporal => []}. establish_subgoal_relationships(SubGoals, _ComplexGoal) -> % Create relationships between sub-goals lists:map(fun(SubGoal) -> #{ subgoal => SubGoal, dependencies => [], prerequisites => [], relationships => [] } end, SubGoals). insert_subgoals_in_hierarchy(SubGoals, _Relationships, Hierarchy) -> % Insert sub-goals into the goal hierarchy lists:foldl(fun(SubGoal, Acc) -> SubGoalId = maps:get(goal_id, SubGoal, generate_goal_id()), maps:put(SubGoalId, SubGoal, Acc) end, Hierarchy, SubGoals). apply_priority_based_resolution(_Conflicts, _State) -> #{}. apply_resource_optimization_resolution(_Conflicts, _State) -> #{}. apply_temporal_scheduling_resolution(_Conflicts, _State) -> #{}. apply_goal_merging_resolution(_Conflicts, _State) -> #{}. apply_goal_postponing_resolution(_Conflicts, _State) -> #{}. apply_general_resolution(_Conflicts, _State) -> #{}. update_goals_from_resolution(_Results, Goals) -> Goals. update_hierarchy_from_resolution(_Results, Hierarchy) -> Hierarchy. prioritize_goals_internal(Goals, _Context, _State) -> Goals. update_goal_priorities(_Results, Goals) -> Goals. analyze_goal_formation_process(_State) -> #{}. identify_improvement_areas(_Analysis, _State) -> []. generate_meta_goals(_Areas, _Context, _State) -> []. analyze_process_effectiveness(_State) -> #{}. identify_process_optimizations(_Analysis, _State) -> []. apply_process_optimizations(_Opportunities, Strategies) -> Strategies. extract_lessons_from_outcome(_GoalId, _Outcome, _State) -> []. update_preferences_from_lessons(_Lessons, Preferences) -> Preferences. update_strategies_from_lessons(_Lessons, Strategies) -> Strategies. create_performance_record(_GoalId, _Outcome, _Lessons) -> #{}. analyze_performance_data(_Data, _State) -> #{}. identify_strategy_adaptations(_Analysis, _State) -> []. apply_strategy_adaptations(_Adaptations, Strategies) -> Strategies. should_form_new_goals(_State) -> true. create_autonomous_context(_State) -> #{}. form_autonomous_goals_internal(_Context, _State) -> {ok, []}. integrate_new_goals(_Goals, State) -> State. get_active_plans(_State) -> []. monitor_plan_progress(_Plan, _State) -> #{}. adapt_plans_based_on_monitoring(_Results, State) -> State. update_resource_state(State) -> State#planning_state.resource_state. check_for_resource_conflicts(_ResourceState, _State) -> []. handle_resource_conflicts_internal(_Conflicts, State) -> State.