Ensemble Case-Based Reasoning: Collaboration Policies for Multiagent Cooperative CBR
ICCBR '01 Proceedings of the 4th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Logical Preference Representation and Combinatorial Vote
Annals of Mathematics and Artificial Intelligence
PARMENIDES: facilitating deliberation in democracies
Artificial Intelligence and Law - AI & law in eGovernment and eDemocracy part I
Learning and joint deliberation through argumentation in multiagent systems
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
A Short Introduction to Computational Social Choice
SOFSEM '07 Proceedings of the 33rd conference on Current Trends in Theory and Practice of Computer Science
Case-based learning from proactive communication
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
| Hi-index | 0.00 |
In this paper we focus on how to use CBR for making collective decisions in groups of agents. Moreover, we show that using CBR allows us to dispense with standard but unrealistic assumptions taken in these kind of tasks. Typically, social choice studies voting methods but assumes complete knowledge over all possible alternatives. We present a more general scenario called open-ended deliberative agreement with rational ignorance (ODARI), and show how can CBR be used to deal with rational ignorance. We will apply this approach to the Banquet Agreement scenario, where two agents deliberate and jointly agree on a two course meal. Rational ignorance makes sense in this scenario, since it would be unreasonable for the agents to know all the alternatives. Unknown alternatives, as well as a strategy to increase chances of reaching an agreement, are problems addressed using case-based methods.