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Much research in artificial intelligence is concerned with the development of autonomous agents that can interact effectively with other agents. An important aspect of such agents is the ability to reason about the behaviours of other agents, by constructing models which make predictions about various properties of interest (such as actions, goals, beliefs) of the modelled agents. A variety of modelling approaches now exist which vary widely in their methodology and underlying assumptions, catering to the needs of the different sub-communities within which they were developed and reflecting the different practical uses for which they are intended. The purpose of the present article is to provide a comprehensive survey of the salient modelling methods which can be found in the literature. The article concludes with a discussion of open problems which may form the basis for fruitful future research. [ABSTRACT FROM AUTHOR]

A review of popular technology adoption models identified several factors that are likely to influence Voice Activated Personal Assistant (VAPA) use in public spaces. To inform design decisions of how to make the private use of the VAPA in public spaces more acceptable from the users’ point of view, an online survey was conducted to investigate the likelihood of usage of the smartphone VAPA such as Apple’s Siri (compared to the usage of smartphone keyboard) as a function of location (private vs. public) and type of information (private vs. nonprivate). Responses from participants showed that users were more cautious of transmitting private than nonprivate information. This effect of type of information was amplified in the social context of public locations and when using conspicuous methods of information input such as the VAPA. Participants also preferred using the VAPA in private locations and showed no preference of location for keyboard entries. Correlations between likelihood of usage of VAPA and the social acceptability ratings were positive and predicted similar patterns of smartphone usage. [ABSTRACT FROM PUBLISHER]

The article presents a study on the collective social strategies for the diffusion of multiagents. It highlights the use of two kinds of diffusions which are the collective insurgence, as well as the elite diffusions that are modelled through setting the variables in the formal framework. It explores the concurrent forms of collective diffusion, while social strategies are determined by other diffusion processes on other agents. It focuses on the spatial diffusion model assuming that all agents can be found in an Euclidian space wherein the social distances between agents can be measured.

We coordinate in discrete time the interaction of two heterogeneous groups of mobile agents: a group of ground vehicles (ugvs) and a group of aerial vehicles (uavs). The ground agents interact with each other through time-invariant, nearest-neighbour rules. They synchronize their velocities through a specific communication protocol, and maintain cohesion and separation behaviour by means of interagent potential forces. Ground vehicles estimate their formation’s centroid using only locally available delayed information. That same information is transmitted to the aerial group, which orbits above the ground formation’s centroid, while avoiding midair collisions. Stability of the ground group motion is established in a Lyapunov framework. A Lyapunov analysis is also used to ensure that uavs track the ground group’s centroid. [Copyright &y& Elsevier]

PROSOCS agents are software agents that are built according to the KGP model of agency. KGP is used as a model for the mind of the agent, so that the agent can act autonomously using a collection of logic theories, providing the mind's reasoning functionalities. The behavior of the agent is controlled by a cycle theory that specifies the agent's preferred patterns of operation. The implementation of the mind's generic functionality in PROSOCS is worked out in such a way so it can be instantiated by the platform for different agents across applications. In this context, the development of a concrete example illustrates how an agent developer might program the generic functionality of the mind for a simple application. [ABSTRACT FROM AUTHOR]

The paper introduces some issues and related solutions adopted in order to realize the MMASS platform. This is a framework to specify and execute simulation applications based on the multi-layered multi-agent situated system model (MMASS). MMASS is a model for multi-agent systems (MAS) situated in an environment whose structure is explicitly defined. The behavior and interaction models of MMASS agents are strongly related to the spatial structure of their environment. The MMASS model is the result of a long-term research that has its roots and motivations on application domains and problems that require spatial features to be considered. Our experiences with these problems have concerned the design of domain models and their implementations, according to the MAS approach for simulation purposes. This activity has revealed that currently available tools do not support the management of spatial features of agent environment and interaction mechanisms defined by the MMASS model and thus they are not suitable for our purposes. The paper focuses on the MMASS platform that aims to support the specification and development of applications (mainly, simulations) based on MMASS. Design issues and related solutions that have been adopted in order to manage those aspects that characterize the MMASS model will be shown. After a description of the conceptual model that underlies the MMASS platform and its general architecture, we will overview how the platform supports the specification of agent structured environment, behavior and interaction, and how it supports the execution of agent actions and interactions. Then we will describe issues and adopted solutions (both algorithmic and implementative ones) to manage at-a-distance interaction among MMASS agents. [ABSTRACT FROM AUTHOR]

Enabling and managing coordination activities between autonomous, possibly mobile, computing entities in dynamic computing scenarios challenges traditional approaches to distributed application development and software engineering. This paper specifically focuses on the problem of motion coordination, and proposes field-based coordination as a general framework to model and engineer such coordinated behaviors. The key idea in field-based coordination is to have agents' movements driven by computational force fields, generated by the agents themselves and/or by some infrastructure, and propagated across the environment. This paper shows that field-based approaches enable the definition of adaptive and effective motion coordination schemes, which can be modeled and tested by making use of a dynamical systems formalism, and which can be easily implemented either above existing middleware infrastructures or by making use of novel middleware specifically conceived for field-based coordination. [ABSTRACT FROM AUTHOR]

The evolution of powerful portable networked devices allows nomadic users seamless access to business and leisure information any time and any where. This drives service infrastructures to similarly evolve to meet new service management challenges in order to adapt information delivery to a richer spatial, temporal, and user context whilst balancing the concerns of the different stakeholders. This paper presents the use of a multi-agent system service infrastructure and associated privacy model to maintain the balance between the service provider's need to maximize its knowledge of the user context against the need for the user's privacy to be protected. [ABSTRACT FROM AUTHOR]

Multi-agent systems are well suited for building large software systems. A great deal of these complex systems includes process flows that are concerned with time or are even time-critical. The activities of these process flows are often executed in distributed autonomous subsystems that have to be synchronized with respect to the superordinated task execution. To be able to build such systems and test their behavior adequately, it is often advantageous and sometimes necessary to simulate them in the run-up to their practical use. Testing and simulation of process flows within multi-agent systems requires synchronization of the participating agents with respect to the global simulation time. In this paper, a design proposal and a service implementation for time management is presented, which takes care of the special requirements imposed by multi-agent settings. This so-called time service is implemented as an FIPA-compliant agent, and can be used to couple heterogeneous subsystems implemented on different agent platforms. [ABSTRACT FROM AUTHOR]

In this paper we present the agent architecture development environment (ADE), intended for the design, implementation, and testing of distributed robotic agent architectures. ADE is unique among robotic architecture development environments in that it is based on a universal agent architecture framework called APOC, which allows it to implement architectures in any design methodology, and in that it uses an underlying multi-agent system to allow for the the distribution of architectural components over multiple host computers. After a short exposition of the theory behind ADE, we present the multi-agent system setup and give an example of using ADE in a multi-robot setting. A general discussion then highlights some of the novel features of ADE and illustrates how ADE can be used for designing, implementing, testing, and running agent architectures. [ABSTRACT FROM AUTHOR]

In order to harness complexity in multi-agent systems (MAS), first-class entities that mediate interaction between agents and environment are required, which can encapsulate control over MAS behavior and evolution. To this end, MAS infrastructures should provide mediating artifacts , both enabling and constraining agent interactions, and possibly representing admissible agent perceptions and actions over the environment. Along this line, in this paper, we take the notion of agent coordination context (ACC) as a means to model agent-environment interactions, and show how it can be embedded within a MAS infrastructure in terms of model and runtime structures. Then, we take the TuCSoN coordination infrastructure as a reference, and extend it with the ACC abstraction to integrate the support for coordination with organization and security. [ABSTRACT FROM AUTHOR]

This paper investigates a human walking behavior- based mobile robot control system. The Intelligent Space (iSpace) is a distributed sensory system, which is the background infrastructure to observe human walking in a limited area. The observation of human walking behavior is applied to train fuzzy-neural networks (FNN). The trained FNNs are applied to approximate the obstacle avoidance behavior of human walking. The paper introduces the iSpace and the mobile agents, which are mobile robots, utilizing the intelligence of the iSpace. The observed and trained human walking behaviors are applied to control the mobile agent in a human-robot shared environment. Experimental results demonstrate the effectiveness of the FNN-based control system. [ABSTRACT FROM AUTHOR]

The ability for a given agent to adapt on-line to better interact with another agent is a difficult and important problem. This problem becomes even more difficult when the agent to interact with is a human, because humans learn quickly and behave nondeterministically. In this paper, we present a novel method whereby an agent can incrementally learn to predict the actions of another agent (even a human), and thereby can learn to better interact with that agent. We take a case-based approach, where the behavior of the other agent is learned in the form of state–action pairs. We generalize these cases either through continuousk-nearest neighbor, or a modified bounded minimax search. Through our case studies, our technique is empirically shown to require little storage, learn very quickly, and be fast and robust in practice. It can accurately predict actions several steps into the future. Our case studies include interactive virtual environments involving mixtures of synthetic agents and humans, with cooperative and/or competitive relationships. [ABSTRACT FROM AUTHOR]