This paper presents an agent strategy for complex bilateral negotiations over many issues with inter-dependent valuations. We use ideas inspired by graph theory and probabilistic ...
Valentin Robu, D. J. A. Somefun, Johannes A. La Po...
Reinforcement Learning (RL) is the study of programs that improve their performance by receiving rewards and punishments from the environment. Most RL methods optimize the discoun...
We present negotiation schemes for efficient role adoption that enhance utility in organizations. In one scheme, local utility computations determine role adoption. In the second ...
Abstract. We propose a logic-based approach to automated oneshot multi-issue bilateral negotiation. We use logic in two ways: (1) a logic theory to represent relations among issues...
Azzurra Ragone, Tommaso Di Noia, Eugenio Di Sciasc...
This paper describes our study into the concept of using rewards in a classifier system applied to the acquisition of decision-making algorithms for agents in a soccer game. Our a...