We present a prototype of agent-based intrusion detection system designed for deployment on high-speed backbone networks. The main contribution of the system is the integration of...
Synthetically generated 3D humans often fail to express a full range of emotions or present different levels of the same type of emotion. Transcending the facial expression, what ...
Agents programmed in BDI-inspired languages have goals to achieve and a library of plans that can be used to achieve them, typically requiring further goals to be adopted. This is...
Patricia H. Shaw, Berndt Farwer, Rafael H. Bordini
The aim of transfer learning is to accelerate learning in related domains. In reinforcement learning, many different features such as a value function and a policy can be transfer...
This paper extends existing methods for information searching and sharing in large-scale, dynamic networks of agents, to deal with networks of heterogeneous agents: Agents that do...
The goal of Reinforcement learning (RL) is to maximize reward (minimize cost) in a Markov decision process (MDP) without knowing the underlying model a priori. RL algorithms tend ...
We report the implementation and evaluation of a Simulation Theory (ST) approach to the Theory of Mind in intelligent graphical agents driven by an affective agent architecture FA...
The paper formalizes a distributed approach to the problem of supervising the execution of a multi-agent plan where (possibly joint) actions are executed concurrently by a team of...