Social influence, negotiation and cognition

To understand how personal agreements can be generated within complexly differentiated social systems, we develop an agent-based computational model of negotiation in which social influence plays a key role in the attainment of social and cognitive integration. The model reflects a view of social influence that is predicated on the interactions among such factors as the agents' cognition, their abilities to initiate and maintain social behaviour, as well as the structural patterns of social relations in which influence unfolds. Findings from a set of computer simulations of the model show that the degree to which agents are influenced depends on the network of relations in which they are located, on the order in which interactions occur, and on the type of information that these interactions convey. We also find that a fundamental role in explaining influence is played by how inclined the agents are to be concilatory with each other, how accurate their beliefs are, and how self-confident they are in dealing with their social interactions. Moreover, the model provides insights into the trade-offs typically involved in the exercise of social influence

The organisation of sociality: a manifesto for a new science of multi-agent systems

In this paper, we pose and motivate a challenge, namely the need for a new science of multi-agent systems. We propose that this new science should be grounded, theoretically on a richer conception of sociality, and methodologically on the extensive use of computational modelling for real-world applications and social simulations. Here, the steps we set forth towards meeting that challenge are mainly theoretical. In this respect, we provide a new model of multi-agent systems that reflects a fully explicated conception of cognition, both at the individual and the collective level. Finally, the mechanisms and principles underpinning the model will be examined with particular emphasis on the contributions provided by contemporary organisation theory

Social Influence and the Generation of Joint Mental Attitudes in Multi-agent Systems

This work examines the social structural and cognitive foundations of joint mental attitudes in complexly differentated multi-agent systems, and incorporates insights from a variety of disciplines, including mainstream Distributed Artificial Intelligence, sociology, administrative science, social psychology, and organisational perspectives. At the heart of this work lies the understanding of the on-going processes by which socially and cognitively differentiated agents come to be socially and cognitively integrated. Here we claim that such understanding rests on the consideration of the nature of the influence processes that affect socialisation intensity. To this end, we provide a logic-based computational model of social influence and we undertake a set of virtual experiments to investigate whether and to what extent this process, when it is played out in a system of negotiating agents, results in a modification of the agents' mental attitudes and impacts on negotiation performance

Social Mental Shaping: Modelling the Impact of Sociality on Autonomous Agents' Mental States

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 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

Evolutionary stability of behavioural types in the continuous double auction

In this paper, we investigate the effectiveness of different types of bidding behaviour for trading agents in the Continuous Double Auction (CDA). Specifically, we consider behavioural types that are neutral (expected profit maximising), passive (targeting a higher profit than neutral) and aggressive (trading off profit for a better chance of transacting). For these types, we employ an evolutionary game-theoretic analysis to determine the population dynamics of agents that use them in different types of environments, including dynamic ones with market shocks. From this analysis, we find that given a symmetric demand and supply, agents are most likely to adopt neutral behaviour in static environments, while there tends to be more passive than neutral agents in dynamic ones. Furthermore, when we have asymmetric demand and supply, agents invariably adopt passive behaviour in both static and dynamic environments, though the gain in so doing is considerably smaller than in the symmetric case

Using Similarity Criteria to Make Negotiation Trade-Offs

This paper addresses the issues involved in software agents making trade-offs during automated negotiations in which they have information uncertainty and resource limitations. In particular, the importance of being able to make trade-offs in real-world applications is highlighted and a novel algorithm for performing trade-offs for multi-dimensional goods is developed. The algorithm uses the notion of fuzzy similarity in order to find negotiation solutions that are beneficial to both parties. Empirical results indicate the benefits and effectiveness of the trade-off algorithm in a range of negotiation situations

Automated Negotiation for Provisioning Virtual Private Networks Using FIPA-Compliant Agents

This paper describes the design and implementation of negotiating agents for the task of provisioning virtual private networks. The agents and their interactions comply with the FIPA specification and they are implemented using the FIPA-OS agent framework. Particular attention is focused on the design and implementation of the negotiation algorithms

Autonomous Agents for Business Process Management

Traditional approaches to managing business processes are often inadequate for large-scale organisation-wide, dynamic settings. However, since Internet and Intranet technologies have become widespread, an increasing number of business processes exhibit these properties. Therefore, a new approach is needed. To this end, we describe the motivation, conceptualization, design, and implementation of a novel agent-based business process management system. The key advance of our system is that responsibility for enacting various components of the business process is delegated to a number of autonomous problem solving agents. To enact their role, these agents typically interact and negotiate with other agents in order to coordinate their actions and to buy in the services they require. This approach leads to a system that is significantly more agile and robust than its traditional counterparts. To help demonstrate these benefits, a companion paper describes the application of our system to a real-world problem faced by British Telecom

Detection and emotional evaluation of an electric vehicle’s exterior sound in a simulated environment

Electric vehicles are quiet at low speeds and thus potentially pose a threat to pedestrians’ safety. Laws are formulating worldwide that mandate these vehicles emit sounds to alert the pedestrians of the vehicles’ approach. It is necessary that these sounds promote a positive perception of the vehicle brand, and understanding their impact on soundscapes is also important. Detection time of the vehicle sounds is an important measure to assess pedestrians’ safety. Emotional evaluation of these sounds influences assessment of the vehicle brand. Laboratory simulation is a new approach for evaluating exterior automotive sounds. This study describes the implementation of laboratory simulation to compare the detection time and emotional evaluation of artificial sounds for an electric vehicle. An Exterior Sound Simulator simulated audio-visual stimuli of an electric car passing a crossroad of a virtual town at 4.47 ms-1 (10 mph), from the perspective of a pedestrian standing at the crossroad. In this environment, 15 sounds were tested using experiments where participants detected the car and evaluated its sound using perceptual dimensions. Results show that these sounds vary significantly in their detection times and emotional evaluations, but crucially that traditional metrics like dB(A) do not always relate to the detection of these sounds. Detection time and emotional evaluation do not have significant correlation. Hence, sounds of a vehicle could be detected quickly, but may portray negative perceptions of the vehicle. Simulation provides a means to more fully evaluate potential electric vehicle sounds against the competing criteria

Using Intelligent Agents to Manage Business Processes

This paper describes work undertaken in the ADEPT (Advanced Decision Environment for Process Tasks) project towards developing an agent-based infrastructure for managing business processes. We describe how the key technology of negotiating, service providing, autonomous agents was realised and demonstrate how this was applied to the BT business process of providing a customer quote for network services