A Multiagent Framework for Human Coalition Formation. Nobel Khandaker and Leen-Kiat Soh. Goal of the paper. Framework for an Agent Assisted Human Coalition Formation. The HCFP Problem.
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A Multiagent Framework for Human Coalition Formation Nobel Khandaker and Leen-Kiat Soh
Goal of the paper • Framework for an Agent Assisted Human Coalition Formation
The HCFP Problem • Given a set H of human users and a set T of tasks, the HCFP is to partition H into coalitions C1, C2, …,Cj such that C1 ∩ C2 ∩ … ∩ Cj = Ø and the coalitions optimizes current-task rewards of all human users over all the entire set of tasks.
Background • Multiagent Coalition Formation Techniques not readily applicable. Why ? • HCFP comes with a number of problems : • Human changes due to learning: Can acquire new skills • Rewards : associated with current and future tasks • Uncertainty in human behavior: MAS must be able to model this uncertainty
Assumptions • About HCFP: Task, Coalition, Behavior, Learning, Uncertainty and Reward • About Environment: Assumptions 7 - 17
The MHCF Problem • Essentially the same as HCFP problem but constrained by the environmental assumptions. The problem is • computationally intractable • Waste resources trying to compute optimal reward • They argue that using sequential rational decision, near optimal coalition can be achieved • Optimal coalition is not feasible due to uncertainty in human behavior
The MHCF Problem for Individual Agent Similar to the general MHCF but from the perspective of an individual agent trying to construct an optimize coalition sequentially. Scaffolding ?
The MHCF Framework • Negotiation : Initialization, Negotiation and Finalization • Negotiation is a three-stage process: proposition, consideration and notification • During proposition: Agent can (a) Relinquish its turn (b) Propose modification to its coalition with a renewed demand (c ) propose to form new coalition with other new members • Consideration: Accept proposal, Reject proposal or provide a counter proposal
The MHCF Framework • Learning: Human users learn from their experience • Agents learn about modeling the human user more accurately
Implementation • They carried out some simulation using SimCol A multiagent application for simulating collaborative learning of a set of students in the Computer-Supported Collaborative Learning(CSCL) environment. They also provide some experimental results