1. 1 Multi-Agent Planning

2. 2 Tasks as Agents negotiating for resources Self-interested Selfish Agents Complexity of Negotiation Tasks Abstraction & Analysis I need resource X …

3. 3 Tasks as Agents negotiating for resources Self-interested Selfish Agents Self-interested Collaborating Agents Complexity of Negotiation Tasks Abstraction & Analysis 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 enable other agents to use it later …

4. 4 Tasks as Agents negotiating for resources Self-interested Selfish Agents Self-interested Collaborating Agents Global Welfare Oriented Collaborating Agents Complexity of Negotiation Tasks Abstraction & Analysis 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 enable other agents to use it later … I need resource X, and it will allow us to improve our joint success … I need resource X, and it will allow us to improve our joint success …

5. 5 Tasks as Agents negotiating for resources Self-interested Selfish Agents Self-interested Collaborating Agents Global Welfare Oriented Collaborating Agents Complexity of Negotiation Tasks Abstraction & Analysis Distributed Constraint Satisfaction Distributed Planning with Conjunctive Goals Distributed (Hierarchical) Planning with Disjunctive Goals Technology Reusage

6. 6 Distributed Constraint Satisfaction Distributed Planning with Conjunctive Goals Distributed (Hierarchical) Planning with Disjunctive Goals Formal Modeling & Complexity Analysis More and more important! 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

7. Exploiting Structure is Crucial! Poly- time NP-completePSPACE-completeEXPTIME-complete 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. Hybrid Scheduling & Planning

8. Example (Nasa) Planning is hard: find right sequence of actions 10 actions, 10! = 3 x 10 6 Contingency planning is really hard: 10 224 possible plans! 10 x 9 2 x 8 4 x 7 8 x … x 2 256