Brian Logan

Building cognitively rich agents using the SIM_Agent toolkit

Synthetic agents with varying degrees of intelligence and autonomy are being designed in many research laboratories. The motivations include military training simulations, games and entertainments, educational software, digital personal assistants, software agents managing Internet transactions or purely scientific curiosity. Different approaches are being explored, including, at one extreme, research on the interactions between agents, and at the other extreme research on processes within agents. The first approach focuses on forms of communication, requirements for consistent collaboration, planning of coordinated behaviours to achieve collaborative goals, extensions to logics of action and belief for multiple agents, and types of emergent phenomena when many agents interact, for instance taking routing decisions on a telecommunications network. The second approach focuses on the internal architecture of individual agents required for social interaction, collaborative behaviours, complex decision making, learning, and emergent phenomena within complex agents. Agents with complex internal structure may, for example, combine perception, motive generation, planning, plan execution, execution monitoring, and even emotional reactions. We expect the second approach to become increasingly important for large multi-agent systems deployed in networked environments, as the level of intelligence required of individual agents increases. This is particularly relevant to work on agents which must cooperate to perform tasks requiring planning, problem solving, learning, opportunistic redirection of plans, and fine judgement, in a partially unpredictable environment. In such contexts, important new information about something other than the current goal can arrive at unexpected times or be found in unexpected contexts, and there is often insufficient time for deliberation. This requires reactive mechanisms. However some tasks involve achieving new types of goals or acting in novel contexts, which may require deliberative mechanisms. Dealing with conflicting goals, or adapting to changing opportunities and cultures may require sophisticated motivational mechanisms. Motivations for such research include: an interest in modelling human mental functioning (e.g., emotions), a desire for more interesting synthetic agents (‘believable agents’) in games and computer entertainments, and the need for intelligent agents capable of performing more complex tasks than hitherto.

Griefing in virtual worlds: causes, casualties and coping strategies

A virtual world is a computer‐simulated three‐dimensional environment. They are increasingly being used for social and commercial interaction, in addition to their original use for game playing. This paper studies negative behaviour, or ‘griefing’, inside one virtual world through a series of observations and focus groups with users. Data were collected to identify griefing behaviours and their impact, examine why griefing happens and who the likely targets and perpetrators are, and suggest strategies for coping with it. Findings show that griefing behaviour is common. It is defined as unacceptable, persistent behaviour and is typically targeted at inexperienced residents by those with more knowledge of the virtual world. Community and individual coping strategies are identified and discussed.

Design as intelligent behaviour: An AI in design research programme☆

Abstract Design is a kind of intelligent behaviour: a kind which makes much use of explicit knowledge. This paper presents the philosophy, aims, background, experimental approach, of the AI in Design research programme being conducted in the Department of Artificial Intelligence, Edinburgh University. It structures this presentation in terms of the three levels, or kinds, of understanding that Artificial Intelligence research should generate; Knowledge Level, Symbol Level, and System Engineering Level understanding. The development of an exploration-based model of design is presented at the Knowledge Level, an AI-based design support system architecture is presented at the Symbol Level, and the engineering of a series of experimental design support systems is presented at the System Engineering Level. To illustrate the use of the current version of the design support system a water turbine design problem is considered. A final section discusses the current status and future of the research programme.

Distributed simulation of agent-based systems with HLA

In this article we describe HLA_AGENT, a tool for the distributed simulation of agent-based systems, which integrates the SIM_AGENT agent toolkit and the High Level Architecture (HLA) simulator interoperability framework. HLA_AGENT offers enhanced simulation scalability and allows interoperation with other HLA-compliant simulators, promoting simulation reuse. Using a simple Tileworld example, we show how HLA_AGENT can be used to flexibly distribute a SIM_AGENT simulation so as to exploit available computing resources. We present experimental results that illustrate the performance of HLA_AGENT on a Linux cluster running a distributed version of Tileworld and compare this with the original nondistributed SIM_AGENT version.

A Complete and Decidable Logic for Resource-Bounded Agents

We propose a context-logic style formalism, Timed Reasoning Logics (TRL), to describe resource-bounded reasoners who take time to derive consequences of their knowledge. The semantics of TRL is grounded in the agentýs computation, allowing an unambiguous ascription of the set of formulas which the agent actually knows at time t. We show that TRL can capture various rule application and conflict resolution strategies that a rule-based agent may employ, and analyse two examples in detail: TRL(STEP) which models an all rules at each cycle strategy similar to that assumed in step logic [5], and TRL(CLIPS) which models a single rule at each cycle strategy similar to that employed by the CLIPS [22] rule based system architecture.We prove a general completeness and decidability results for TRL(STEP).

Agent based genetic algorithm employing financial technical analysis for making trading decisions using historical equity market data

This work investigates the effectiveness of an agent based trading system. The system developed employs a simple genetic algorithm to evolve an optimized trading approach for every agent, with their trading decisions based on a range of technical indicators generating trading signals. Their trading pattern follows a simple fitness function of maximizing net assets for every evolutionary cycle. Their performance is analyzed compared to market movements as represented by its index, as well as investment funds run by human professionals to establish a relative measure of success. The results show that the developed system performs comparably to its human counterparts across different market environments, despite these agents being rather primitive in nature. Future forthcoming work refines and explores the potential of this approach further.

Logic for coalitions with bounded resources1

Recent work on Alternating-Time Temporal Logic and Coalition Logic has allowed the expression of many interesting properties of coalitions and strategies. However there is no natural way of expressing resource requirements in these logics. This paper presents a Resource-Bounded Coalition Logic (RBCL) which has explicit representation of resource bounds in the language, and gives a complete and sound axiomatisation of RBCL.

Griefing in a Virtual Community An Exploratory Survey of Second Life Residents

Building on the research of Chesney, Coyne, Logan, and Madden (2009), this paper examines griefing within the virtual online community of Second Life via an online survey of 86 residents (46% men). Results suggested that griefing was deemed to be an unacceptable, persistent negative behavior which disrupted enjoyment of the environment and which was experienced by 95% of the sample, with 38% classified as frequent victims and 20% classified as perpetrators. No differences emerged in rates between gender (real life and second life), age, and time as a resident in Second Life. A number of self, player- and game-influenced motivations were judged to promote griefing, with respondents overall split on the impact of griefing when compared to traditional bullying. Further, respondents felt that a shared responsibility to control griefing was needed with individuals, residents as a community, and Second Life developers all playing a part. Discussion of the findings in relation to cyber-bullying in general is pre...

Modularity and compositionality in Jason

In this paper, we present our experiences using the Jason agentoriented programming language to develop a complex multi-agent application. We highlight a number of shortcomings in the current design of the language when building complex agents, and propose revisions to the language to allow the development of modular programs that facilitate code reuse and independent development. In particular, we propose a mechanism for modular construction of agents from functionally encapsulated components, and discuss alterations to the belief base language to enable more robust software engineering.

An adaptive load management mechanism for distributed simulation of multi-agent systems

The paper presents a load management mechanism for distributed simulations of multi-agent systems. The mechanism minimizes the cost of accessing the shared state in the distributed simulation by dynamically redistributing shared state variables according to the access pattern of the simulation model. To evaluate the effectiveness and performance of the mechanism, a series of benchmark experiments were performed using the PDES-MAS framework for distributed simulation of multi-agent systems. Although preliminary, the results indicate that the proposed mechanism significantly reduces the overall access cost of the system.