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

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

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 B1 G B2 B4B3 G1G2 B1B2 B3 B5 B4B6

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

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

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 G B1B2 B3 B4 B5 G B1B2 G B1 B3B2 Stream 1 Stream 2 Stream 3 D

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

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