Reinforcement learning (RL) is one of the machine learning techniques and has been received much attention as a new self-adaptive controller for various systems. The RL agent auto...
We consider the problem of Adverse Selection and optimal derivative design within a Principal-Agent framework. The principal’s income is exposed to non-hedgeable risk factors ar...
Abstract. The formalization and use of experiences in good model design would make an important contribution to increasing the efficiency of modeling as well as to supporting the k...
This paper introduces HealthAgents, an EC-funded research project to improve the classification of brain tumours through multi-agent decision support over a distributed network o...
To increase the believability and life-likeness of Embodied Conversational Agents (ECAs), we introduce a behavior synthesis technique for the generation of expressive gesturing. A...