Mobile Agents in Interaction Spaces

Mobile agent systems are difficult to reason about and implement efficiently and safely. Theoretical work, most notably process calculi, provide solid semantics for mobile systems. However, the theory is often too abstract to match with the requirements of practical implementations. To fill this gap, intermediate models must be proposed. We present in this paper such a model named Interaction Spaces, a metaphor of geometrical spaces in which agents interact through simple transformations. The framework captures high-level distributed semantics, most notably asynchronous, multicast communications on FIFO channels. It also refines and implements the channel passing feature of the pi-calculus, together with the mobility of agent themselves. Above interaction spaces, we propose a full-fledged agent calculus and its associated operational semantics.     

Markovian Search Games in Heterogeneous Spaces

In this paper, we consider how to search for a mobile evader in a large heterogeneous region when sensors are used for detection. Sensors are modeled using probability of detection. Due to environmental effects, this probability will not be constant over the entire region. We map this problem to a graph-search problem, and even though deterministic graph search is NP-complete, we derive a tractable optimal probabilistic search strategy. We do this by defining the problem as a dynamic game played on a Markov chain. We prove that this strategy is optimal in the sense of Nash. Simulations of an example problem illustrate our approach and verify our claims.     

Improving Performance of Heterogeneous Agents

Agents provide services not only to humans users but also to agents in one or more multiagent systems. When agents are confronted with multiple tasks to perform (or requests to satisfy), the agent can reduce load on itself by attempting to take advantage of commonalities between the tasks that need to be performed. In this paper, we develop a logical theory by which such “heavily loaded” agents can merge commonalities amongst such tasks. In our framework, agents can be built on top of legacy codebases. We propose a logical formalism called invariants using which agent developers may specify known commonalities between tasks – after this, we propose a sound and complete mechanism to derive all possible derived commonalities. An obvious A ^*-based algorithm may be used to merge a set of tasks in a way that minimised expected execution cost. Unfortunately the execution time of this algorithm is prohibitive, even when only 10 tasks need to be merged, thus making it unusable in practice. We develop heuristic algorithms for this problem that take much less time to execute and produce almost as good ways of merging tasks.     

A Simulation Framework for Heterogeneous Agents

We introduce a generic simulation framework suitable for agent-based simulations featuring the support of heterogeneous agents, hierarchical scheduling, and flexible specification of design parameters. One key aspect of this framework is the design specification: we use a format based on the Extendible Markup Language (XML) that is simple-structured yet still enables the design of flexible models. Another issue in agent-based simulations, especially when ready-made components are used, is the heterogeneity arising from both the agents' implementations and the underlying platforms. To tackle such obstacles, we introduce a wrapper technique for mapping the functionality of agents living in an interpreter-based environment to a standardized JAVA interface, thus facilitating the task for any control mechanism (like a simulation manager) because it has to handle only one set of commands for all agents involved. Again, this mapping is made by an XML-based definition format. We demonstrate the technique by applying it to a simple sample simulation of two mass marketing firms operating in an artificial consumer environment.     

Asset Price Dynamics among Heterogeneous Interacting Agents

In this paper, we investigate the presence of rationalherding on asset price dynamics during the intra-day trading withheterogeneous interacting agents, whose information set is notcomplete. In the model, individual probability measures offinancial investment strategies are defined using statisticalmechanics concepts. In addition, there is a learning processtoward the best strategy, implemented as a geneticalgorithm. Simulations show that imitative behavior can be arational strategy, since it allows an investor to gain excessreturns on an asset by exploiting information regarding pricedynamics not strictly contained in the fundamental solution. Herdbehavior is rational in the sense that it produces profits at theexpense of increasing the complexity of the system.     

Network Formation with Heterogeneous Agents and Absolute Friction

We present a model of strategic network formation with absolute friction and heterogeneous agents. The individual payoffs from a given network are determined by the difference of an agent specific utility function that depends on the number of her direct links and the sum of her link-costs. These link-costs decompose in a symmetric function that represents the social distance between the two agents and an agent specific function representing the partner’s quality. From a theoretical point of view, we analyze strong pairwise stable networks (Belleflamme and Bloch, Int Econ Rev 45(2):387–411, 2004) and show that our model always has a unique strong pairwise stable network which is also strongly stable (Dutta and Mutuswami, J Econ Theory, 76:322–344, 1997). From a practical point of view, we provide an algorithm that reproduces this stable network from information on the individual payoff structure. We illustrate the use of this algorithm by applying it to an informal risk sharing network data set from the village of Nyakatoke in rural Tanzania.     

Interactive Navigation of Heterogeneous Agents Using Adaptive Roadmaps

We present a novel algorithm for collision-free navigation of a large number of independent agents in complex and dynamic environments. We introduce adaptive roadmaps to perform global path planning for each agent simultaneously. Our algorithm takes into account dynamic obstacles and interagents interaction forces to continuously update the roadmap based on a physically-based dynamics simulator. In order to efficiently update the links, we perform adaptive particle-based sampling along the links. We also introduce the notion of 'link bands' to resolve collisions among multiple agents. In practice, our algorithm can perform real-time navigation of hundreds and thousands of human agents in indoor and outdoor scenes.     

Larks: Dynamic Matchmaking Among Heterogeneous Software Agents in Cyberspace

Service matchmaking among heterogeneous software agents in the Internet is usually done dynamically and must be efficient. There is an obvious trade-off between the quality and efficiency of matchmaking on the Internet. We define a language called Larks for agent advertisements and requests, and present a flexible and efficient matchmaking process that uses Larks. The Larks matchmaking process performs both syntactic and semantic matching, and in addition allows the specification of concepts (local ontologies) via ITL, a concept language. The matching process uses five different filters: context matching, profile comparison, similarity matching, signature matching and constraint matching. Different degrees of partial matching can result from utilizing different combinations of these filters. We briefly report on our implementation of Larks and the matchmaking process in Java. Fielded applications of matchmaking using Larks in several application domains for systems of information agents are ongoing efforts.     

一种基于移动Agent的异构网络管理模型

分析了集中式网络管理方法的局限性,介绍了移动Agent的特点及与传统方法相比的优势,提出了一种针对异构网络的基于移动Agent的网管模型,详细地介绍了该模型的设计思想、结构、管理方式及安全性、容错性、独立性等特点。设计实现了两种移动Agent:故障诊断代理和故障搜索代理。使用它们评估和验证了移动A gent管理实际的异构网络的能力,它们能够在一个特定大小的网络中准确定位故障并分析故障的原因。     

Complementarity Modeling of a Ramsey-Type Equilibrium Problem with Heterogeneous Agents

We contribute to the field of Ramsey-type equilibrium models with heterogeneous agents. To this end, we state such a model in a time-continuous and time-discrete form, which in the latter case leads to a finite-dimensional mixed complementarity problem. We prove the existence of solutions of the latter problem using the theory of variational inequalities and present further properties of its solutions. Finally, we compute the growth dynamics in a calibrated model in which households differ with respect to their relative risk aversion, their discount factors, their initial wealth, and with respect to their interest rates on savings.

     

An Automated Teamwork Infrastructure for Heterogeneous Software Agents and Humans

Agent integration architectures enable a heterogeneous, distributed set of agents to work together to address problems of greater complexity than those addressed by the individual agents themselves. Unfortunately, integrating software agents and humans to perform real-world tasks in a large-scale system remains difficult, especially due to three main challenges: ensuring robust execution in the face of a dynamic environment, providing abstract task specifications without all the low-level coordination details, and finding appropriate agents for inclusion in the overall system. To address these challenges, our Teamcore project provides the integration architecture with general-purpose teamwork coordination capabilities. We make each agent team-ready by providing it with a proxy capable of general teamwork reasoning. Thus, a key novelty and strength of our framework is that powerful teamwork capabilities are built into its foundations by providing the proxies themselves with a teamwork model.Given this teamwork model, the Teamcore proxies addresses the first agent integration challenge, robust execution, by automatically generating the required coordination actions for the agents they represent. We can also exploit the proxies' reusable general teamwork knowledge to address the second agent integration challenge. Through team-oriented programming, a developer specifies a hierarchical organization and its goals and plans, abstracting away from coordination details. Finally, KARMA, our Knowledgeable Agent Resources Manager Assistant, can aid the developer in conquering the third agent integration challenge by locating agents that match the specified organization's requirements. Our integration architecture enables teamwork among agents with no coordination capabilities, and it establishes and automates consistent teamwork among agents with some coordination capabilities. Thus, team-oriented programming provides a level of abstraction that can be used on top of previous approaches to agent-oriented programming. We illustrate how the Teamcore architecture successfully addressed the challenges of agent integration in two application domains: simulated rehearsal of a military evacuation mission and facilitation of human collaboration.     

Situated Interaction in Art

This paper describes metaphors and design strategies used to conceive and develop a hand-held, location-aware tourist guide that delivers information related to the surrounding space mainly by reacting to the physical movements of the visitors. The guide is designed to minimise the boundary between the physical space and the related information through a number of situated and contextual-aware interaction mechanisms. These mechanisms are conceived to support the activity both at individual and social level.     

Transition Dynamics in a Network Game with Heterogeneous Agents: the Stochastic Case

Automation and Remote Control - Stochastic parameters are introduced into a model of network games with production and knowledge externalities. The model was formulated by V. Matveenko and A....     

The Role of Heterogeneous Agents’ Past and Forward Time Horizons in Formulating Computational Models

The conditioning of strategies by market environment and the simultaneous emergence of market structure in the presence of evolving trading strategies are investigated with major international stock indexes. Models for price forecasting and trading strategies evolution are examined under different time horizons. The results demonstrate that trading strategies can become performative in thin markets, thereby shaping the price dynamics, which in turn feeds back into the strategy. The dominance in thin markets by some (short-memory) traders produces a better environment for learning profitable strategies with computational intelligence tools.The experiment conducted contradicts assertions that long-term fitness of traders is not a function of an accurate prediction, but only of an appropriate risk aversion through a stable saving rate. The stock traders’ economic performance is found to be best with a 1-year forward time horizon, and it deteriorates significantly for tests with horizons exceeding 2 years, identifying frequent structural breaks. To model the turmoil in an economic system with recurrent shocks, short-memory horizons are optimal, as older data is not informative about current or future states.     

Situated multimodal interaction in S K

In this paper, we give a short overview of the S K system, a flexible and adaptive multimodal dialog system. The system uses a common dialog backbone to realize three interaction scenarios. Through the use of generic methods and knowledge sources for multimodal fusion and fission, we were able to develop a generic dialog system for flexible multimodal interaction.     

Entertaining Situated Messaging at Home

Leisure and entertainment-based computing has been traditionally associated with interactive entertainment media and game playing, yet the forms of engagement offered by these technologies only support a small part of how we act when we are at leisure. In this paper, we move away from the paradigm of leisure technology as computer-based entertainment consumption, and towards a broader view of leisure computing. This perspective is more in line with our everyday experience of leisure as an embodied, everyday accomplishment in which people artfully employ the everyday resources in the world around them in carrying out their daily lives outside of work. We develop this extended notion of leisure using data from a field study of domestic communication focusing on asynchronous and situated messaging to explore some of these issues, and develop these findings towards design implications for leisure technologies. Central to our discussion on the normal, everyday and occasioned conduct of leisure lie the notions of playfulness and creativity, the interweaving of the worlds of work and leisure, and in the creation of embodied displays of affect, all of which may be seen manifested in the use of messaging artefacts. This view of technology in support of leisure-in-the-broad is strongly divergent from traditional entertainment computing models in its coupling of the mechanics of the organisation of everyday life to the ways that we make entertainment for ourselves. This recognition allows us to draw specific implications for domestic situated messaging technologies, but also more generally for technology design by tying activities that we tend to regard as purely functional to other multifaceted and leisure-related purposes.