This paper presents CBRetaliate, an agent that combines Case-Based Reasoning (CBR) and Reinforcement Learning (RL) algorithms. Unlike most previous work where RL is used to improve...
Bryan Auslander, Stephen Lee-Urban, Chad Hogg, H&e...
This work presents a new approach that allows the use of cases in a case base as heuristics to speed up Multiagent Reinforcement Learning algorithms, combining Case-Based Reasoning...
It is useful for an intelligent software agent to be able to adapt to new demands from an environment. Such adaptation can be viewed as a redesign problem; an agent has some origin...
The goal of transfer learning is to use the knowledge acquired in a set of source tasks to improve performance in a related but previously unseen target task. In this paper, we pr...
Manu Sharma, Michael P. Holmes, Juan Carlos Santam...
In this paper we propose an approach to address the old problem of identifying the feature conditions under which a gaming strategy can be effective. For doing this, we will build ...
Chad Hogg, Stephen Lee-Urban, Bryan Auslander, H&e...