Alert-BDI: BDI Model with Adaptive Alertness through Situational Awareness

In this paper, we address the problems faced by a group of agents that possess situational awareness, but lack a security mechanism, by the introduction of a adaptive risk management system. The Belief-Desire-Intention (BDI) architecture lacks a framework that would facilitate an adaptive risk management system that uses the situational awareness of the agents. We extend the BDI architecture with the concept of adaptive alertness. Agents can modify their level of alertness by monitoring the risks faced by them and by their peers. Alert-BDI enables the agents to detect and assess the risks faced by them in an efficient manner, thereby increasing operational efficiency and resistance against attacks.Comment: 14 pages, 3 figures. Submitted to ICACCI 2013, Mysore, Indi

Radical Agent-based Approach for Intelligence Analysis

This paper presents a novel agent-based framework as a decision aid tool for intelligence analysis. This technology extends net-centric information processing and abstraction as well as fusion and multi-source integration strategies. Our information agents traverse and mediate disparate ontologies in different formats providing a foundation for semantic interoperability. The presented system provides knowledge discovery by accessing a large number of information sources in a particular domain and organizing them into a network of information agents. Each agent provides expertise on a specific topic by drawing on relevant information from other information agents in related knowledge domains. Unique advantages include net-centric scalability, principled information assurance, as well as ground breaking knowledge discovery in service of intelligence analysis

Weaving a fabric of socially aware agents

The expansion of web-enabled social interaction has shed light on social aspects of intelligence that have not been typically studied within the AI paradigm so far. In this context, our aim is to understand what constitutes intelligent social behaviour and to build computational systems that support it. We argue that social intelligence involves socially aware, autonomous individuals that agree on how to accomplish a common endeavour, and then enact such agreements. In particular, we provide a framework with the essential elements for such agreements to be achieved and executed by individuals that meet in an open environment. Such framework sets the foundations to build a computational infrastructure that enables socially aware autonomy.This work has been supported by the projects EVE(TIN2009-14702-C02-01) and AT (CSD2007-0022)Peer Reviewe

Formal Agent Development: Framework to System

Much work in the field of agent-based systems has tended to focus on either the development of practical applications of agent systems on the one hand, or the development of sophisticated logics for reasoning about agent systems on the other. Our own view is that work on formal models of agent-based systems are valuable inasmuch as they contribute to a fundamental goal of computing of practical agent development. In an ongoing project that has been running for several years, we have sought to do exactly that through the development of a formal framework that provides a conceptual infrastructure for the analysis and modelling of agents and multi-agent systems on the one hand, and enables implemented and deployed systems to be evaluated and compared on the other. In this paper, we describe our research programme, review its achievements to date, and suggest directions for the future

Simplifying the development of intelligent agents

Intelligent agents is a powerful Artificial Intelligence technology which shows considerable promise as a new paradigm for mainstream software development. However, despite their promise, intelligent agents are still scarce in the market place. A key reason for this is that developing intelligent agent software requires significant training and skill: a typical developer or undergraduate struggles to develop good agent systems using the Belief Desire Intention (BDI) model (or similar models). This paper identifies the concept set which we have found to be important in developing intelligent agent systems and the relationships between these concepts. This concept set was developed with the intention of being clearer, simpler, and easier to use than current approaches.We also describe briefly a (very simplified) example from one of the projects we have worked on (RoboRescue), illustrating the way in which these concepts are important in designing and developing intelligent software agents

An AgentSpeak meta-interpreter and its applications

A meta-interpreter for a language can provide an easy way of experimenting with modifications or extensions to a language. We give a meta-interpreter for the AgentSpeak language, prove its correctness, and show how the meta-interpreter can be used to extend the AgentSpeak language and to add features to the implementation

BDI reasoning with normative considerations

F. Meneguzzi thanks Fundaç ao de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS, Brazil) for the financial support through the ACI program (Grant ref. 3541-2551/12-0) and the ARD program (Grant ref. 12/0808-5), as well as Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) through the Universal Call (Grant ref. 482156/2013-9) and PQ fellowship (Grant ref. 306864/2013-4). N. Oren and W.W. Vasconcelos acknowledge the support of the Engineering and Physical Sciences Research Council (EPSRC, UK) within the research project “Scrutable Autonomous Systems” (SAsSY11, Grant ref. EP/J012084/1).Peer reviewedPostprin

Detecting and avoiding interference between goals in intelligent agents

Pro-active agents typically have multiple simultaneous goals. These may interact with each other both positively and negatively. In this paper we provide a mechanism allowing agents to detect and avoid a particular kind of negative interaction where the effects of one goal undo conditions that must be protected for successful pursuit of another goal. In order to detect such interactions we maintain summary information about the definite and potential conditional requirements and resulting effects of goals and their associated plans. We use these summaries to guard protected conditions by scheduling the execution of goals and plan steps. The algorithms and data structures developed allow agents to act rationally instead of blindly pursuing goals that will conflict

Implementasi Logika Fuzzy Untuk Pilot Agent Dalam Simulator Pengendali Lalu Lintas Udara (ATC Simulator)

Pilot agent memungkinkan objek pesawat di dalam sebuah simulator pengendali lalu lintas udara memiliki tingkah laku (behaviour). Pilot agent dalam simulator ini dirancang untuk dapat merespon gejala cuaca yang diberikan oleh administrator atau instruktur sebelum simulator dijalankan. Respon pilot agent terhadap cuaca buruk kemudian ditampilkan sebagai suatu permasalahan yang harus diatasi oleh pengguna simulator. Gejala cuaca buruk yang akan digunakan dalam penelitian ini adalah wet microburst. Pilot dalam dunia nyata memperkirakan kemungkinan munculnya wet microburst dengan memperhatikan visualisasi cuaca di sekitarnya dan laporan cuaca yang diterima. Parameter gejala wet microburst yang digunakan dibatasi pada parameter intensitas hujan dan perbedaan suhu udara dengan titik embun (dew point spread).  Respon pilot agent dibangun menggunakan metode penalaran Fuzzy Reasoning. Hasil reasoning yang dihasilkan dalam penelitian ini selanjutnya dibandingkan dengan hasil reasoning MATLAB untuk mengetahui apakah algoritma yang dihasilkan berjalan dengan baik. Dari hasil perbandingan menunjukkan reasoning yang dihasilkan dalam penelitian ini berjalan dengan baik