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Modeling Teamwork in MultiAgent Systems: The CAST Architecture

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Title: Modeling Teamwork in MultiAgent Systems: The CAST Architecture


1
Modeling Teamwork in Multi-Agent Systems The
CAST Architecture
  • Dr. Thomas Ioerger, Jianwen Yin, and Michael
    Miller
  • Computer Science, Texas AM University
  • March 21, 2001

2
Agenda
  • Teamwork
  • CAST
  • MALLET
  • DIARG
  • Dynamic Role Selection
  • Conclusions

3
What is a Team?
  • Definition of a Team
  • A group of entities that are working together to
    achieve a shared (or common) goal
  • Team needs
  • Coordination
  • Sharing of information
  • Distributed decision-making
  • Focus of (human) teamwork optimizations
  • Situational awareness
  • Communications efficiency
  • Effectiveness of group decision-making

4
Previous work on Teamwork
  • Multi-agent teams
  • Cohen Levesques joint intention theory
  • Planning and plan specification/recognition
  • Team-oriented programming
  • STEAM based on SOAR by Tambe based on
    joint-intentions
  • Groszs Shared Plans
  • Psy. Research on Human Team-Training
  • Shared mental models

5
Issues in Multi-Agent Team Training System Design
  • How to represent a team? (Team ontology and
    MALLET)
  • How to effectively reason about other team
    members roles and beliefs to collaborate?
  • How to initiate communication? (DIARG)

6
Shared Mental Model
  • Team structure roles
  • responsibilities for individual steps in plans
  • mutual belief assumption
  • Team process team plan
  • use Petri Nets as an approximate finite and
    computable model of team process
  • use the token flow in Petri Nets to monitor and
    track the plan execution)

B
A
start
D
end
C
7
From teamwork to agent model
  • A compositional multi-agent architecture

8
CAST (Collaborative Agents for Simulating
Teamwork)
  • Model effective teamwork by capturing team
    structures and teamwork process
  • Enable agents in a team to have flexibility for
    adapting the team to changes in the environment

9
CAST Architecture
10
MALLET (Multi-Agent Logic Language for Encoding
Teamwork)
  • Basic Object Type Predicates
  • Actions and Plans
  • Responsibilities
  • Capabilities
  • Belief
  • Communication

11
MALLET Specification
  • Team plans
  • role specifications (with constraints)
  • process specification

(team-plan make-dinner (?entrée) (role shopper
?X (has-money ?X)) (role cook ?Y
) (process (if (need-ingredients
?entree) (sequence (do ?X (go-to store))
(do ?X (buy-ingredients ?entrée))) (parall
el (do ?Y (prepare ?entrée)) (do ?X
set-table)) (forall ?Z (team-member ?Z) (do ?Z
eat)) (do-all (clean-up dishes)))) // an AND
team-operator
12
Team Operators
  • Joint actions coop-mode
  • and lifting a couch together
  • xor/or hitting a volleyball
  • Team operator
  • team, co-mode, arguments
  • precond, postcond

13
Responsibilities
  • Responsibilities are relationships between a set
    of roles, a goal, and a stage, represented as
    Responsibility(ltrole-setgt, ltgoalgt, stage)
  • Redundant responsibilities Or-
    responsibility(ltrole-setgt, ltgoalgt, stage)
  • Shared competitive responsibilities
    Xor-responsibility(ltrole-setgt, ltgoalgt, stage)
  • Shared complementary responsibilities And-
    responsibility(ltrole-setgt, ltgoalgt, stage)

14
Capabilities
  • Capabilities are relationships between roles and
    actions, which is represented as
    Capability(ltrole-setgt, ltactiongt)
  • Backup capability Or- capability(ltrole-setgt,
    ltactiongt)
  • Shared competitive capability Xor-
    capability(ltrole-setgt, ltactiongt)
  • Shared conflicting capability And-
    capability(ltrole-setgt, ltactiongt)

15
Three Major Algorithms
  • Petri Net generation algorithm
  • DIARG
  • Dynamic role selection

16
Petri Nets
  • place/transition Petri nets vs. PrT nets
  • propositional ? first-order predicate
  • PrT nets vs. logic programs
  • happy(x) ? cat(x), purrs(x).
  • Concurrence
  • Firing rule vs. meta-predicates

17
Petri Net Generation
  • Sequential process
  • Parallel process

18
Petri Net Generation (Cont.)
  • If process

sub-net
Then cond
else cond
sub-net
start
end
19
DIARG (Dynamic Inter-Agent Rule Generator)
  • Proactive information exchange
  • inferring what might be needed for others to
    complete their (current) tasks
  • Proactively provide timely information
  • Reduce communication overhead
  • Examines needers and providers of information in
    order to allow dynamic generation of information
    flow

20
Dynamic Role Selection
  • Whenever there is a choice on who performs an
    action (i.e.role redundancy)
  • Postpone role selection until reach the
    individual plan or individual operator level
  • Might need to communicate to
  • resolve ambiguities of responsibility
  • synchronize for joint actions
  • Advantages
  • Provide flexibility in team formation
  • Others can play backup role, in case of failure
  • Improve teamwork efficiency, Balance workload

21
Future Work
  • Simulating more dynamic teams
  • handling failures, load-balancing, delegation,
    unreliable agents
  • Handling more types of communication
  • resolving conflicting information
  • situation assessment (cognitive models)
  • Reasoning about agent capabilities
  • Goal regression and planning
  • User-modeling inferring state/beliefs/intent
    from monitoring actions

22
Conclusions
  • First version (CAST 1.0) running now
  • see demo
  • Target domains Team Training
  • AWACS
  • Fire Fighting
  • Army Brigade Operations Staff
  • NASA Flight Controllers

23
Acknowledgements
  • Dr. Richard Volz, Dr. John Yen, Dr. Dianxiang Xu
  • Heejin Lim, Sen Cao, Yue Zhou, Xueqi Cheng, Colby
    Johnson
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