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Agent Architectures
Published in Weiming Shen, Douglas H. Norrie, Jean-Paul A. Barthès, Multi-Agent Systems for Concurrent Intelligent Design and Manufacturing, 2019
Weiming Shen, Douglas H. Norrie, Jean-Paul A. Barthès
As noted in Section 6.4.1.1, most deliberative agent models are based on Newell and Simon’s physical symbol system hypothesis (Newell and Simon, 1976). Recently, research on deliberative agents has explored the modeling of agents based on beliefs, desires, and intentions. Architectures following this paradigm have become known as BDI (Belief, Desire, and Intention) architectures. Basic concepts of the BDI architectures date back to Bratman (1987) and to the Procedural Reasoning System (PRS) by Georgeff and Lansky (1986). Subsquently, this has become a strong research area for agent design, see e.g., (Rao and Georgeff, 1991; 1992; 1995).
Automatic Error Detection and Recovery
Published in Ulrich Rembold, Robot Technology and Applications, 2020
A method that combines task planning with reaction to sensor data, developed by Georgeff [37], uses knowledge about the task to guide the interpretation of sensor data. Georgeff [37,56] and his group have designed the PRS (procedural reasoning system) system to allow reactive reasoning. PRS keeps procedures instead of generating plans every time, so reducing the work the planner has to perform. This allows the system to operate in real time. Other planners take too long to replan, which means that reactions to unexpected events may come too late. The PRS system in a sense is more like an operating system than a planner.
BASTA: BDI-based architecture of simulated traffic agents
Published in Journal of Information and Telecommunication, 2020
Inga Rüb, Barbara Dunin-Kȩplicz
Meta desires in Basta can be compared to metalevel Knowledge Areas proposed in Procedural Reasoning System (Georgeff & Ingrand, 1989). Firstly, they influence the internal state of an agent. Secondly, both mechanisms are applicable only in certain situations. But, while PRS agents have to perform unification of all FOL formulas in order to choose the correct metalevel KA, in Basta this process is much more efficient. The algorithm of a meta desire simply goes through branch instructions to the block that defines the right behaviour in given circumstances. It does not have to consider all predefined functions – as soon as a particular condition is examined, the set of potential procedures is narrowed down to methods that meet the requirement.
ALAS: agent-oriented domain-specific language for the development of intelligent distributed non-axiomatic reasoning agents
Published in Enterprise Information Systems, 2018
Dejan Sredojević, Milan Vidaković, Mirjana Ivanović
JADEX (2017) is a BDI reasoning engine whose architecture for the development of intelligent agents is based on Procedural Reasoning System. JADEX agents communicate by exchanging messages. Within JADEX platform, intelligent agents can be programmed using XML or Java language. JADEX reasoning engine is very flexible and can be used in various environments. It is most commonly used within the JADE (2017) platform which is one of the most popular agent environments that are currently available to the open source community (Bellifemine, Caire, and Greenwood 2007).