This chapter addresses embodied social interaction inlif6 like agents. Embodiment is discussedf rom both arti cial intelligence and psychology viewpoints. Di#erent degreesof embodiment in biological, virtual and robotic agents are discussed, given the example of a bottomup, behavior-oriented, dynamic control of virtual robots. A `dancing with strangers' experiment shows how the same principles can be applied to physical robot-human interaction. We then discuss the issue of sociality which di#ers in di#erent academic communities with respect to which roles are attributed to genes, memes, and the individual embodied agent.

We describe the use of the mobile agent paradigm to design an improved infrastructure for data integration in distributed sensor network (DSN). We use the acronym MADSN to denote the proposed mobileagent -based DSN. Instead of moving data to processing elements for data integration, as is typical of a client/server paradigm, MADSN moves the processing code to the data locations. This saves network bandwidth and provides an effective means for overcoming network latency, since large data transfers are avoided. Our major contributions are the use of mobile agent in DSN for distributed data integration and the evaluation of performance between DSN and MADSN approaches. We develop an enhanced multiresolution integration (MRI) algorithm where multiresolution analysis is applied at local node before accumulating the overlap function by mobile agent. Compared to the MRI implementation in DSN, the enhanced integration algorithm saves up to 90% of the data transfer time. We develop objective functions to evaluation the performance between DSN and MADSN approaches. For a given set of network parameters, we analyze the conditions under which MADSN performs better than DSN and determine the condition under which MADSN reaches its optimum performance level.

Teamwork is a critical capability in multi-agent environments. Many such environments mandate that the agents and agent-teams must be persistent i.e., exist over long periods of time. Agents in such persistent teams are bound together by their long-term common interests and goals. This paper focuses on flexible teamwork in such persistent teams. Unfortunately, while previous work has investigated flexible teamwork, persistent teams remain unexplored. For flexible tamwork, one promising approach that has emerged is model-based, i.e., providing agents with general models of teamwork that explicitly specify their commitments in teamwork. Such models enable agents to autonomously reason about coordination. Unfortunately, for persistent teams, such models may lead to coordination and communication actions that while locally optimal, are highly problematic for the team's long-term goals. We present a decisiontheoretic technique to enable persistent teams to overcome such limitations of the m...

Agent-Oriented Software Engineering (AOSE) is an emerging paradigm within industry that offers much potential of the management of the increasing levels of complexity inherent within modern software systems. For this paradigm to gain widespread acceptance, it is vital that we develop comprehensive frameworks that support the development and deployment of agent-oriented applications. This thesis contributes to this through the development of a four-tier development framework entitled the Agent Factory System. This framework combines an agent programming language that is founded upon a formal agent theory of commitment; a run-time environment that delivers a set of services that support the deployment of agent-oriented applications written in this programming language; an integrated development environment that delivers a toolkit that supports the development of these applications; and a development methodology that promotes a structure approach to the use of this toolkit. Finally, we evaluate the Agent Factory System from the context of various real-world

A hand-designed internal representation of the world cannot deal with unknown or uncontrolled environments. Motivated by human cognitive and behavioral development, this paper presents a theory, an architecture, and some experimental results for developmental robotics. By a developmental robot, we mean that the robot generates its “brain ” (or “central nervous system, ” including the information processor and controller) through online, real-time interactions with its environment (including humans). A new Self-Aware Self-Effecting (SASE) agent concept is proposed, based on our SAIL and Dav developmental robots. The manual and autonomous development paradigms are formulated along with a theory of representation suited for autonomous development. Unlike traditional robot learning, the tasks that a developmental robot ends up learning are unknown during the programming time so that the task-specific representation must be generated and updated through real-time “living ” experiences. Experimental results with SAIL and Dav developmental robots are presented, including visual attention selection, autonomous navigation, developmental speech learning, range-based obstacle avoidance, and scaffolding through transfer and chaining.

this document. 9.5.2 A comparison of CUE and libido

We summarize selected recent developments and promising directions for improving the quality of models of human performance in synthetic environments. The potential uses and goals for behavioral models in synthetic environments are first summarized. Within that context, we examine relevant, current work related to modeling more complete performance, for example, on cognitive modeling of emotion, advanced techniques for testing and building models of behavior, new cognitive architectures, and agent and Belief, Desires and Intentions (BDI) technology. The report also considers the usability of these systems as an important but neglected aspect of their performance. A list of projects with high payoff for modeling human performance in synthetic environments is noted.

This paper presents a framework that captures how the social nature of agents that are situated in a multi-agent environment impacts upon their individual mental states. Roles and social relationships provide an abstraction upon which we develop the notion of social mental shaping. This allows us to extend the standard Belief-Desire-Intention model to account for how common social phenomena (e.g. cooperation, collaborative problem-solving and negotiation) can be integrated into a unified theoretical perspective that reflects a fully explicated model of the autonomous agent’s mental state. Keywords: Multi-agent systems, agent interactions, BDI models, social influence. 2 1.

Introduction This chapter presents the agent-based perspective on imitation. In this perspective, imitation is best considered as the behavior of an autonomous agent in relation to its environment, including other autonomous agents. We argue that such a perspective helps unfold the full potential of research on imitation and helps in identifying challenging and important research issues. We first explain the agent-based perspective and then discuss it in the context of particular research issues in studies with animals and artifacts, with reference to chapters presented in this book. At the end of the chapter we briefly introduce the individual contributions to this book and provide a roadmap that helps the reader in navigating through the exciting and highly interwoven themes that are presented in this book. In order to focus discussions, we explain the agent-based perspective with particular consideration of the correspondence

Abstract. In this paper we overview one specific approach to the formal development of multi-agent systems. This approach is based on the use of temporal logics to represent both the behaviour of individual agents, and the macro-level behaviour of multi-agent systems. We describe how formal specification, verification and refinement can all be developed using this temporal basis, and how implementation can be achieved by directly executing these formal representations. We also show how the basic framework can be extended in various ways to handle the representation and implementation of agents capable of more complex deliberation and reasoning.