Compositional design and reuse of a generic agent model

This article introduces a formally specified design of a compositional generic agent model (GAM). This agent model abstracts from specific application domains; it provides a unified formal definition of a model for weak agenthood. It can be (re) used as a template or pattern for a large variety of agent types and application-domain types. The model was designed on the basis of experiences in a number of application domains. The compositional development method DESIRE was used to design the agent model GAM at a conceptual and logical level. It serves as a unified, precisely defined, conceptual structure, which can be refined by specialization and instantiation to a large variety of other, more specific agents. To illustrate reuse of this agent model, specialization and instantiation to model cooperative information gathering agents is described in depth. Moreover, it is shown how GAM can be used to describe in a unified and, hence, more comparable manner a large number of agent architectures from the literature.     

The adversarial activity model for bounded rational agents

Multiagent research provides an extensive literature on formal Beliefs-Desires-Intentions (BDI) based models describing the notion of teamwork and cooperation. However, multiagent environments are often not cooperative nor collaborative; in many cases, agents have conflicting interests, leading to adversarial interactions. This form of interaction has not yet been formally defined in terms of the agents mental states, beliefs, desires and intentions. This paper presents the Adversarial Activity model, a formal Beliefs-Desires-Intentions (BDI) based model for bounded rational agents operating in a zero-sum environment. In complex environments, attempts to use classical utility-based search methods with bounded rational agents can raise a variety of difficulties (e.g. implicitly modeling the opponent as an omniscient utility maximizer, rather than leveraging a more nuanced, explicit opponent model). We define the Adversarial Activity by describing the mental states of an agent situated in such environment. We then present behavioral axioms that are intended to serve as design principles for building such adversarial agents. We illustrate the advantages of using the model as an architectural guideline by building agents for two adversarial environments: the Connect Four game and the Risk strategic board game. In addition, we explore the application of our approach by analyzing log files of completed Connect Four games, and gain additional insights on the axioms’ appropriateness.     

The complexity of agent design problems: Determinism and history dependence

The agent design problem is as follows: given a specification of an environment, together with a specification of a task, is it possible to construct an agent that can be guaranteed to successfully accomplish the task in the environment? In this article, we study the computational complexity of the agent design problem for tasks that are of the form “achieve this state of affairs” or “maintain this state of affairs.” We consider three general formulations of these problems (in both non-deterministic and deterministic environments) that differ in the nature of what is viewed as an “acceptable” solution: in the least restrictive formulation, no limit is placed on the number of actions an agent is allowed to perform in attempting to meet the requirements of its specified task. We show that the resulting decision problems are intractable, in the sense that these are non-recursive (but recursively enumerable) for achievement tasks, and non-recursively enumerable for maintenance tasks. In the second formulation, the decision problem addresses the existence of agents that have satisfied their specified task within some given number of actions. Even in this more restrictive setting the resulting decision problems are either pspace-complete or np-complete. Our final formulation requires the environment to be history independent and bounded. In these cases polynomial time algorithms exist: for deterministic environments the decision problems are nl-complete; in non-deterministic environments, p-complete.     

Can a rational agent afford to be affectless? a formal approach

In this article, we expose some of the issues raised by the critics of the neoclassical approach to rational agent modeling and we propose a formal approach for the design of artificial rational agents that includes some of the functions of emotions found in the human system. We suggest that emotions and rationality are closely linked in the human mind (and in the body, for that matter) and, therefore, need to be included in architectures for designing rational artificial agents, whether these agents are to interact with humans, to model humans' behaviors and actions, or both. We describe an Affective Knowledge Representation (AKR) scheme to represent emotion schemata, which we developed to guide the design of a variety of socially intelligent artificial agents. Our approach focuses on the notion of "social expertise" of socially intelligent agents in terms of their external behavior and internal motivational goal-based abilities. AKR, which uses probabilistic frames, is derived from combining multiple emotion theories into a hierarchical model of affective phenomena useful for artificial agent design. AKR includes a taxonomy of affect, mood, emotion, and personality, and a framework for emotional state dynamics using probabilistic Markov Models.     

ADE: STEPS TOWARD A DISTRIBUTED DEVELOPMENT AND RUNTIME ENVIRONMENT FOR COMPLEX ROBOTIC AGENT ARCHITECTURES

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.     

A HYBRID ARCHITECTURE FOR DISTRIBUTED AUTONOMOUS CONTROL AGENTS

Abstract

Business environments, like most other real systems, are distributed in nature. However, the fact that the environment itself is distributed does not justify a distributed control architecture. On the other hand, a centralized architecture is not exactly an ideal form of control. The architecture proposed herein is a hybrid control architecture that maps the decision-making environment of many situations ranging from factory floors to traffic control. The architecture assumes the presence of self-reliant (autonomous) decision-making agents, which are required to respond in a certain amount of time. Cooperation between these agents is assumed, and therefore each agent is expected to perform as best as it can in order to complete a well-defined task. No central coordination or control agent is assumed. Thus an asynchronous behavior is assumed.     

Using bayesian networks to model agent relationships

An agent-society of the future is envisioned to be as complex as a human society. Just like human societies, such multiagent systems (MAS) deserve an in-depth study of the dynamics, relationships, and interactions of the constituent agents. An agent in a MAS may have only approximate a priori estimates of the trustworthiness of another agent. But it can learn from interactions with other agents, resulting in more accurate models of these agents and their dependencies together with the influences of other environmental factors. Such models are proposed to be represented as Bayesian or belief networks. An objective mechanism is presented to enable an agent elicit crucial information from the environment regarding the true nature of the other agents. This mechanism allows the modeling agent to choose actions that will produce guaranteed minimal improvement of the model accuracy. The working of the proposed maxim in entropy procedure is demonstrated in a multiagent scenario.     

Composing web services enacted by autonomous agents through agent-centric contract net protocol

ContextAgents are considered as one of the fundamental technologies underlying open and dynamic systems that are largely enabled by the semantic web and web services. Recently, there is a trend to introduce the notion of autonomy empowered by agents into web services. However, it has been argued that the characteristics of autonomy will make agents become available intermittently and behave variedly over time, which therefore increase the complexity on devising mechanisms for composing services enacted by autonomous agents.ObjectiveIn this work, we propose an extension to Contract Net protocol, called Agent-centric Contract Net Protocol (ACNP), as a negotiation mechanism with three key features for composing web services enacted by autonomous agents.Method(1) A matchmaking mechanism embedded in a middle agent (as a service matchmaker) for discovering web services that are available intermittently is presented based on the concept of agent roles; (2) A selection algorithm based on risk-enabled reputation model (REAL) embedded in a manager agent (as a service composer) is introduced to serve a basis for selecting web services with variant performance; and (3) A negotiation mechanism between a manager agent and contractor agents (as atomic services) is devised and enables both a service composer and the atomic services to request, refuse or agree on adapting changes of services.ResultsThe problem of assembling a computer is discussed in this paper.ConclusionIt is increasingly recognised that web services would become more autonomous by introducing diverse agent technologies to better constitute more complex systems in open and dynamic environments. As web service technologies are best exploited by composite services, it is imperative to devise mechanisms for composing services of autonomy.     

Agent组织中的政策导向型协作模型

传统Agent协作模型强调Agent的高度自主性,其自发协作过程完全出于内部的"自私性"动机,难以在模型中表达宏观层面上的引导及系统外部的约束,在应用于开放复杂软件系统时,将面临可信度不能满足要求、计算复杂度高及没有有效的冲突消解机制这3方面的问题,这阻碍了Agent技术在现实软件系统建模中的应用.采用组织与政策隐喻,提出Agent组织中的政策导向型协作模型,通过组织与政策给予Agent以宏观上的引导与外部的控制,以增强系统的可信度;采用扩展的可废止逻辑框架,对这一协作过程建立一个具有线性计算复杂度的形式化理论;逻辑体系中内置的优先级方式为系统提供了有效的冲突消解机制.并证明了模型所具有的一致性及其他特性,最后通过一个实例对系统作出验证性说明.     

AGENT COORDINATION CONTEXTS IN A MAS COORDINATION INFRASTRUCTURE

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.     

Between control and creativity: challenging co-creation and social media use in a museum context

Abstract

This article addresses the challenges and limitations of co-creation processes in museums based on an exemplary case of the design of a Danish museum-related campaign on Facebook. The article adds to the ongoing discussion on the paradigm shift in the museum by analysing potential problematical issues of including multiple agents in creative processes in museums. It concludes that it is arduous to establish a truly creative co-creative process, when the design team needs to accommodate to a well-established artistic vision as well as to the limited resources of the museum and the other participants. We argue that one cannot in advance predict or ascertain that social media users will find a campaign compelling and want to participate and engage with the content, even if substantial resources have gone into its creation. Furthermore, the complexity of many art projects is likely to make their dissemination on social media difficult.     

Avatars of the tortoise: life,longevity and simulation

Abstract

We present a new way of dynamically growing and breeding structures in 3D space through swarming agents. Different agent types and the way they evolve over time is specified by a swarm grammar similar to Lindenmayer systems. We expand common L-system string interpretation from a single turtle to a multitude of turtles which behave like a swarm. By describing swarm agents within the framework of formal grammars, we build a bridge from symbolic production systems (rewrite systems) to three-dimensional real-time construction procedures that are executed by reactive and interacting agents which move in simulated physical 3D spaces. We introduce constructor agents, their formal representation in swarm grammars and demonstrate by examples how (1) the swarm rules, (2) the agent parameters and (3) the environ ment can influence the actual construction and growth processes that are initiated and directed by the swarms. In order to facilitate exploration of a large variety of swarm grammars, we apply interactive evolutionary design methods to create swarm grammar sculptures and 3D structures.     

Continual planning and acting in dynamic multiagent environments

In order to behave intelligently, artificial agents must be able to deliberatively plan their future actions. Unfortunately, realistic agent environments are usually highly dynamic and only partially observable, which makes planning computationally hard. For most practical purposes this rules out planning techniques that account for all possible contingencies in the planning process. However, many agent environments permit an alternative approach, namely continual planning, i.e. the interleaving of planning with acting and sensing. This paper presents a new principled approach to continual planning that describes why and when an agent should switch between planning and acting. The resulting continual planning algorithm enables agents to deliberately postpone parts of their planning process and instead actively gather missing information that is relevant for the later refinement of the plan. To this end, the algorithm explictly reasons about the knowledge (or lack thereof) of an agent and its sensory capabilities. These concepts are modelled in the planning language (MAPL). Since in many environments the major reason for dynamism is the behaviour of other agents, MAPL can also model multiagent environments, common knowledge among agents, and communicative actions between them. For Continual Planning, MAPL introduces the concept of of assertions, abstract actions that substitute yet unformed subplans. To evaluate our continual planning approach empirically we have developed MAPSIM, a simulation environment that automatically builds multiagent simulations from formal MAPL domains. Thus, agents can not only plan, but also execute their plans, perceive their environment, and interact with each other. Our experiments show that, using continual planning techniques, deliberate action planning can be used efficiently even in complex multiagent environments.     

THE STROBE MODEL: DYNAMIC SERVICE GENERATION ON THE GRID

This article presents the STROBE model: both an agent representation and an agent communication, model based on a social approach, which means interaction centered. This model represents how agents may realize the interactive, dynamic generation of services on the Grid. Dynamically generated services embody a new concept of service implying a collaborative creation of knowledge, i.e., learning; services are constructed interactively between agents depending on a conversation. The approach consists of integrating selected features from multi-agent systems and agent communication, language interpretation in applicative/functional programming and e-learning/human-learning into a unique, original, and simple view that privileges interactions, including control. The main characteristic of STROBE agents is that they develop a language (environment + interpreter) for each of their interlocutors. The model is inscribed within a global approach, defending a shift from the classical algorithmic (control based) view to problem solving in computing to an interaction-based view of social informatics, where artificial as well as human agents operate by communicating as well as by computing. The paper shows how the model may not only account for the classical communicating agent approaches, but also represent a fundamental advance in modeling societies of agents in particular in dynamic service generation scenarios such as those necessary today on the Web and proposed tomorrow for the Grid. Preliminary concrete experimentations illustrate the potential of the model; they are significant examples for a very wide class of computational and learning situations.     

Role of obligations in multiagent coordination

Carrying out distributed business processes over networks is rapidly shifting the nature of application architectures from the simple command and control client-server model to complex peer-to-peer models supporting dynamic patterns of social interaction and behavior among autonomous, proactive, goal oriented agents. Trusting agents to autonomously make decisions and execute actions on behalf of humans, as part of global business processes, requires both understanding and modeling of the social laws that govern collective behavior and a practically useful operationalization of the models into agent programming tools. In this article we present a solution to these problems based on a representation of obliged and forbidden behavior in an organizational framework, together with an inference method that also decides which obligations to break in conflicting situations. These are integrated into an operational, practically useful agent development language that covers the spectrum from the definition of organizations, roles, agents, obligations, goals, and conversations to inferring and executing coordinated agent behaviors in multiagent applications. The major strength of the approach is the way it supports coordination by exchanging constraints about obliged and forbidden behavior among agents. We illustrate this and the entire system with solution examples to the feature interaction problem in the telecommunications industry and to integrated supply chain management.     

An ACL for a Dynamic System of Agents

In this article we present the design of an ACL for a dynamic system of agents. The ACL includes a set of conversation performatives extended with operations to register, create, and terminate agents. The main design goal at the agent–level is to provide only knowledge–level primitives that are well integrated with the dynamic nature of the system. This goal has been achieved by defining an anonymous interaction protocol which enables agents to request and supply knowledge without considering symbol–level issues concerning management of agent names, routing, and agent reachability. This anonymous interaction protocol exploits a distributed facilitator schema which is hidden at the agent–level and provides mechanisms for registering capabilities of agents and delivering requests according to the competence of agents. We present a formal specification of the ACL and of the underlying architecture, exploiting an algebra of actors, and illustrate it with the help of a graphical notation. This approach provides the basis for discussing dynamic primitives in ACL and for studying properties of dynamic multi agent systems, for example concerning the behavior of agents and the correctness of their conversation policies.     

TOWARD AN ALGEBRAIC THEORY OF COMPLEXITY IN DYNAMIC SYSTEMS

Abstract

Consider a large economy with many agents, each agent may receive messages from other agents upon which he immediately acts producing new messages for other agents, etc. A legitimate question to ask about such a process is what is its complexity (i.e., the complexity of the overall system)?