In this paper, we investigate Reinforcement learning (RL) in multi-agent systems (MAS) from an evolutionary dynamical perspective. Typical for a MAS is that the environment is not ...
Karl Tuyls, Pieter Jan't Hoen, Bram Vanschoenwinke...
Our participation in TREC 2003 aims to adapt the use of the DFR (Divergence From Randomness) models with Query Expansion (QE) to the robust track and the topic distillation task o...
Giambattista Amati, Claudio Carpineto, Giovanni Ro...
Tuning compiler optimizations for rapidly evolving hardware makes porting and extending an optimizing compiler for each new platform extremely challenging. Iterative optimization i...
Grigori Fursin, Yuriy Kashnikov, Abdul Wahid Memon...
We discuss how Case Based Reasoning (CBR) (see e.g. [1], [4]) philosophy of adaptation of some known situations to new similar ones can be realized in rough set framework [5] for c...
As agents begin to perform complex tasks alongside humans as collaborative teammates, it becomes crucial that the resulting humanmultiagent teams adapt to time-critical domains. I...