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Multi-Agent Planning. Complexity of Negotiation Tasks Abstraction & Analysis. Tasks as Agents negotiating for resources. Self-interested Selfish Agents. I need resource X …. Complexity of Negotiation Tasks Abstraction & Analysis. Tasks as Agents negotiating for resources.
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Complexity of Negotiation Tasks Abstraction & Analysis Tasks as Agents negotiating for resources Self-interested Selfish Agents I need resource X …
Complexity of Negotiation Tasks Abstraction & Analysis Tasks as Agents negotiating for resources Self-interested Collaborating Agents Self-interested Selfish Agents I need resource X … I need resource X, and it will enable other agents to use it later …
Complexity of Negotiation Tasks Abstraction & Analysis Tasks as Agents negotiating for resources Global Welfare Oriented Collaborating Agents Self-interested Collaborating Agents Self-interested Selfish Agents I need resource X … I need resource X, and it will enable other agents to use it later … I need resource X, and it will allow us to improve our joint success …
Complexity of Negotiation Tasks Abstraction & Analysis Tasks as Agents negotiating for resources Global Welfare Oriented Collaborating Agents Self-interested Collaborating Agents Self-interested Selfish Agents Distributed Constraint Satisfaction Distributed Planning with Conjunctive Goals Distributed (Hierarchical) Planning with Disjunctive Goals Technology Reusage
Formal Modeling & Complexity Analysis More and more important! Distributed (Hierarchical) Planning with Disjunctive Goals Distributed Planning with Conjunctive Goals Distributed Constraint Satisfaction • As the negotiation systems are getting more complex, we need more and more advanced: • Formal problem modeling & complexity analysis, • Structural analysis, and • Development of scalable generic negotiation protocols
Hybrid Scheduling& Planning Poly-time NP-complete PSPACE-complete EXPTIME-complete Exploiting Structure is Crucial! Scheduling In terms of worst-case computational complexity, mixed scheduling/planning is significantly harder than scheduling. Therefore, need to exploit problem structure to tame computational complexity.
Example (Nasa) Planning is hard: find right sequence of actions 10 actions, 10! = 3 x 106 Contingency planning is really hard: 10224 possible plans! 10 x 92 x 84 x 78 x … x 2256