We investigate the problem of autonomous agents processing pieces of information that may be corrupted (tainted). Agents have the option of contacting a central database for a reliable check of the status of the message, but this procedure is costly and therefore should be used with parsimony. Agents have to evaluate the risk of being infected, and decide if and when communicating partners are ...

Autonomous agents are being increasingly used in a wide range of applications. The agents operate in common environments and, over time, conflicts inevitably occur among them. Negotiation is the predominant process for solving conflicts. Recent growing interest in electronic commerce has also given increased importance to negotiation. This paper presents a generic negotiation mechanism that han...

My thesis aims to contribute towards building autonomous agents that are able to develop what White (1959) called competency over their environment—agents that are able to achieve mastery over their domain and are able to solve new problems as they arise using the knowledge and skills they acquired in the past. While the field of machine learning has made much progress in solving individual, is...

In this paper we present an architecture for decision making of software agents that allows the agent to behave autonomously. Our target area is computational agents — encapsulating various neural networks, genetic algorithms, and similar methods — that are expected to solve problems of different nature within an environment of a hybrid computational multi-agent system. The architecture is base...

AAFID is a distributed intrusion detection architecture and system, developed in CERIAS at Purdue University. AAFID was the ®rst architecture that proposed the use of autonomous agents for doing intrusion detection. With its prototype implementation, it constitutes a useful framework for the research and testing of intrusion detection algorithms and mechanisms. We describe the AAFID architectur...

This paper gives an overview of the bottom-up approach to artificial intelligence (AI), commonly referred to as behavior-oriented AI. The behavior-oriented approach, with its focus on the interaction between autonomous agents and their environments, is introduced by contrasting it with the traditional approach of knowledge-based AI. Different notions of autonomy are discussed, and key problems ...

Although autonomous systems can support a wide variety of application goals, their perceived risk inhibits their deployment. While this problem is traditionally associated with an agent’s skills, we take the novel perspective that the issue is communication. In this view, the agent simply needs a better representation of the user’s interests so that its choices will not produce unintended effec...

A fresh assessment of what autonomous agents are or may aspire to be is presented in the paper. We dismiss the traditional dichotomy between reactive and symbolic architectures. A classiication in terms of the amount of knowledge embedded in the system is made, instead, running from regulatory to planning to adaptive agents. Regulatory agents are implementable as control systems or automata, an...

In this chapter we raise some of the moral issues involved in the current development of robotic autonomous agents. Starting from the connection between autonomy and responsibility, we distinguish two sorts of problems: those having to do with guaranteeing that the behavior of the artificial cognitive system is going to fall within the area of the permissible, and those having to do with endowi...

The paper presents a general architecture for behaviour based control systems for autonomous agents. A number of archi tectural principles are proposed which make it possible to combine reactive control with learning and problem solving in a coherent way. In particular, I investigate the interaction between reinforcement learning, internal world models and dynamic action selection as well as a ...