BehaviorNet An Action Selection Mechanism

1. BehaviorNetAn Action Selection Mechanism Aregahegn Negatu And Conscious Software Research Group

2. Intelligent agents • Agents have • Drives, agenda, primary motivation • Goals, subgoals • Agents live in an environment • Agents continuously act in pursuit of their goals/agenda

3. Behavior • Is a form of response to a specific environmental configuration. • Such responses are modulated by the underlying goals/drives. • Agents can have more than one relevant behavior in a given situation.

4. Action Selection • Agents exhibit multiple behaviors at a time (given situation) – parallel. • Not time sharing. • Behaviors conflict : use same mechanism or shared resource. • Agents have competing behaviors or actions.

5. Action Selection (cont.) • Agents encounter multiple, competing, relevant behaviors to choose from. • The major intelligence of an agent is used to decide “what to do next.” • Franklin: Artificial minds • Thus, the action-selection problem. • MASM: Maes’ Action Selection Mechanism • How to do the Right thing? (Maes,1990).

6. MASM: Behavior • Behavior (Competence module) is like a production rule: • Situation: precondition • Action: (addition, deletion) • Behavior has an activation: a level of strength.

7. MASM: BehaviorNet • BehaviorNet is a digraph. • With Behaviors as nodes, and • Three types of links: • Successor • Predecessor • Conflicter • Links are determined and created by behaviors (local decision).

8. A behavior stream Acknowledged Send an Acknowledge- ment Drive to acknowledge Goal-directing Activation Compose an Acknowledge- ment Get e-mail address Find a Message template Behavior codelets From sideline Environmental activation

9. MASM: Building BehaviorNet B1 a w b y c B3 w r x s y B2 c x d z e

10. MASM: Activation Spreading • Global goals: built-in source of motivation • Environment: Situational relevance. • Behaviors • Activation by successors and predecessors. • Inhibition by conflicters. • Activation spreads in a greedy way.

11. MASM: Algorithm • Loop for ever • Add external activation • from goals & environment. • Spread activation/inhibition among behaviors • Forward activation via successor links • Backward activation via predecessor links • Backward inhibition via conflicter links • Decay: total activation in system is constant. • Behavior fires if: • It’s executable (all it’s preconditions are satisfied). • It’s activation level is over a threshold (theta). • It’s activation is the maximum of such.

12. MASM: Algorithm (cont.) • If one behavior fires, • its activation is set to zero. • Threshold value is reset to default. • If no behavior fires, reduce threshold value by x%. • System “thinks” for one more round and try again.

13. MASM: Tuning the dynamics • Action selection emerges from the dynamics of activation spreading. • Tunable parameters: • Amount of activation injected by environment. • Amount If activation energy injected by goals. • The threshold value, theta.

14. MASM: Characteristics • Thoughtful • Reactive and fast • Situation-oriented and opportunistic. • Goal-oriented. • Persistent: biased to ongoing goal/plan. • Goals interact and avoid conflicts. • Robust. • Some of the characteristics are not independent of each other and are tunable. • Example: thoughtfulness vs. reactive.

15. BehaviorNet in IDA • Is based on MASM. • Introduces variables with instantiation mechanism. • BehaviorNet has: • Drives: built-in primary motivators. • Importance • Intensity • Streams: Action plans for specific problem. • Behaviors • Goals

16. BehaviorNet in IDA (cont.) • Behavior: • Precondition, addition, deletion lists • Activation • Variable slots • Underlying codelets • Goals: • same as behaviors but may not have codelets to underlie them • Satisfaction-condition (continuous, one-time) • Streams are linked as in MASM • Activation spreads as in MASM

17. Stream examples G G1 G2 G B1 B2 B1 B2 B1 B3 B4 B3 B4 B6 B5

18. Stream instantiation • Template stream: • no variables bound • Instantiated stream: • Some or all variables are bound. • Underlying codelets are instantiated • Is part of the dynamics in the active behavior net

19. Example of instantiated streams Stream 1 Drive 1 Drive 2 Two streams in the same context Stream 2

20. IDA’s Architecture Metacognition Database Perception Linear Functional Deliberation Negotiation Write Orders Behavior Net Conceptual & Behavioral Learning “Consciousness” Perception Associative Memory Episodic Memory Emotions

21. Goal context System • Behavior: a goal context. • Stream: a goal context hierarchy. • Executing behavior: Dominant goal context. • Its stream: dominant goal context hierarchy. • BehaviorNet: a hierarchical goal context system.

22. Goal context hierarchy D G Stream 1 B1 B2 B5 B3 B4 Stream 3 G Stream 2 G B1 B1 B2 B2 B3

23. Working with “Consciousness” Behavior Net template B1 B1 B1 G B1 Sky box Stands Working Memory Black board Broadcast Sideline Playing Field

24. C-U-C cycle Behavior Net System Behavior Codelets Environment Internal States Work Space Behavior Priming Codelets Consciousness System Attention Codelets

25. Remarks • Goal hierarchy instantiation • With preattentive or subliminal perception • With conscious event • Motivation • Built-in - drives • Situational • Significance of action has a level of informativeness • Unconscious avoidance of goal conflicts • Action types • unconscious, • consciously mediated, • voluntary • Drives, as the deepest component in the goal hierarchy, are part of self-concept.