This workshop focuses on models and algorithms for multiagent interaction without prior coordination (MIPC). Interaction between agents is the defining attribute of multiagent systems, encompassing problems of planning in a decentralized setting, learning other agent models, composing teams with high task performance, and selected resource-bounded communication and coordination. There is significant variety in methodologies used to solve such problems, including symbolic reasoning about negotiation and argumentation, distributed optimization methods, machine learning methods such as multiagent reinforcement learning, etc. The majority of these well studied methods depends on some form of prior coordination. Often, the coordination is at the level of problem definition. For example, learning algorithms may assume that all agents share a common learning method or prior beliefs, distributed optimization methods may assume specific structural constraints regarding the partition of state space or cost/rewards, and symbolic methods often make strong assumptions regarding norms and protocols. In realistic problems, these assumptions are easily violated — calling for new models and algorithms that specifically address the case of ad hoc interactions. Similar issues are also becoming increasingly more pertinent in human-machine interactions, where there is a need for intelligent adaptive behaviour and assumptions regarding prior knowledge and communication are problematic.
Effective MIPC is most likely to be achieved as we bring together work from many different areas, including work on intelligent agents, machine learning, game theory, and operations research. For instance, game theorists have considered what happens to equilibria when common knowledge assumptions must be violated, agent designers are faced with mixed teams of humans and agents in open environments and developing variations on planning methods in response to this, etc. The goal of this workshop is to bring together these diverse viewpoints in an attempt to consolidate the common ground and identify new lines of attack.
This workshop is the third edition of the MIPC workshop series, previously held at AAAI-15 and AAAI-14.
The workshop will discuss research related to multiagent interaction without prior coordination, as outlined in the workshop description above. A non-exclusive list of relevant topics includes:
We offer a talk-only option for authors of relevant papers that have been published in journals or conference proceedings. Interested authors are encouraged to send their paper (in PDF or PS format) and publication details via e-mail to mipc2016 AT easychair.org. If the paper is deemed relevant for the workshop, we will allocate a presentation slot for the authors in the workshop program.
The Journal of Autonomous Agents and Multi-Agent Systems plans to publish a special issue on Multiagent Interaction without Prior Coordination. While the MIPC workshop is primarily a venue for early ideas and discussion, the special issue is a platform for more developed ("mature") work. We encourage authors of all MIPC workshops, including this one, to submit their extended versions of their workshop papers to the special issue. (Note that there will be no special treatment for authors of MIPC workshops).
| 09:00 - 10:25 | Session 1 (Chair: Katie Genter) |
| 09:00 - 09:15 | Opening Remarks |
| 09:15 - 10:00 | Invited Talk — Michael Bowling |
| 10:00 - 10:25 | Pablo Hernandez-Leal, Matthew E. Taylor, Benjamin Rosman, L. Enrique Sucar, Enrique Munoz de Cote: Identifying and Tracking Switching, Non-stationary Opponents: a Bayesian Approach |
| 10:25 - 11:00 | Coffee Break |
| 11:00 - 12:10 | Session 2 (Chair: Stefano Albrecht) |
| 11:00 - 11:25 | Katie Genter, Peter Stone: Advances in Adding Influencing Agents to a Flock |
| 11:25 - 12:10 | Invited Talk — Gal Kaminka |
| 12:10 - 14:20 | Lunch |
| 14:20 - 15:10 | Session 3 (Chair: Katie Genter) |
| 14:20 - 14:45 | Trevor Sarratt, Arnav Jhala: Policy Communication for Coordination with Unknown Teammates |
| 14:45 - 15:10 | Saad Alqithami, Henry Hexmoor: Measuring Synergy from Benevolence in a Network Organization |
| 15:10 - 16:00 | Coffee Break |
| 16:00 - 17:00 | Session 4 (Chair: Stefano Albrecht) |
| 16:00 - 16:25 | Muthukumaran Chandrasekaran, Yingke Chen, Prashant Doshi: Bayesian Markov Games with Explicit Finite-Level Types |
| 16:25 - 16:50 | Tathagata Chakraborti, Venkata Vamsikrishna Meduri, Vivek Dondeti, Subbarao Kambhampati: A Game Theoretic Approach to Ad-hoc Coalitions in Human-Robot Societies |
| 16:50 - 17:00 | Closing Remarks |
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Michael Bowling Department of Computer Science University of Alberta Website |
Adventures in Implicit Agent Modelling
Abstract:
TBA
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Gal Kaminka Department of Computer Science Bar-Ilan University Website |
Teams, Swarms, Crowds, and Collectives: Special Cases?
Abstract:
Teams of agents and robots, swarms of robots or animals, crowds of people, and collectives (of everything) permeate our technological, biological, and sociological worlds. They have inspired generations of researchers in multi-agent and multi-robot systems. However, much of the research has split along technological and philosophical fault-lines: emergent or planned? communicating or just sensing? globally coordinated, or locally-reactive? rational or procedural? This talk will briefly explore three fronts, which bridge over such fault lines: Cognitive psychology connecting with human crowds, reinforcement learning in swarms connecting with game theory, and Asimov's laws implemented in molecular robots (nanobots). These fronts hint at a broader and deeper science of social intelligence that is still waiting to be discovered.