Interface Agents in Complex Systems

Zachary, Wayne; Mentec, Jean-Christophe Le; Ryder, Joan M.

doi:10.1007/978-1-4613-1447-9_4

Cited by 23 publications

(6 citation statements)

References 9 publications

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“…In addition to this, a different mechanism is responsible for the adoption of the new goals based on dynamically determined priorities [408]. In COGNET and DIARC, selection of a task/goal triggers an execution of the associated procedural knowledge [614,71]. In DSO, the selector module chooses between available actions or decisions to reach current goals and sub-goals [388].…”

Section: Action Selectionmentioning

confidence: 99%

40 years of cognitive architectures: core cognitive abilities and practical applications

2018

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In this paper we present a broad overview of the last 40 years of research on cognitive architectures. To date, the number of existing architectures has reached several hundred, but most of the existing surveys do not reflect this growth and instead focus on a handful of well-established architectures. In this survey we aim to provide a more inclusive and highlevel overview of the research on cognitive architectures. Our final set of 84 architectures includes 49 that are still actively developed, and borrow from a diverse set of disciplines, spanning areas from psychoanalysis to neuroscience. To keep the length of this paper within reasonable limits we discuss only the core cognitive abilities, such as perception, attention mechanisms, action selection, memory, learning, reasoning and metareasoning. In order to assess the breadth of practical applications of cognitive architectures we present information on over 900 practical projects implemented using the cognitive architectures in our list. We use various visualization techniques to highlight the overall trends in the development of the field. In addition to summarizing the current state-of-the-art in the cognitive architecture research, this survey describes a variety of methods and ideas that have been tried and their relative success in modeling human cognitive abilities, as well as which aspects of cognitive behavior need more research with respect to their mechanistic counterparts and thus can further inform how cognitive science might progress.

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Section: Action Selectionmentioning

confidence: 99%

40 years of cognitive architectures: core cognitive abilities and practical applications

2018

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“…Draper Labs also has an agent architecture called ADEPT [62], which represents years of research in autonomous systems. There is also ICARUS [63] and COGNET [64]. Another interesting technology is the PROLOG computer language [65].…”

Section: ) Act-rmentioning

confidence: 99%

A Review of Intelligent Systems Software for Autonomous Vehicles

Long

Hanford

Janrathitikarn

et al. 2007

2007 IEEE Symposium on Computational Intelligence in Security and Defense Applications

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The need for intelligent unmanned vehicles has been steadily increasing. These vehicles could be air-, ground-, space-, or sea-based. This paper will review some of the most common software systems and methods that could be used for controlling such vehicles. Early attempts at mobile robots were confined to simple laboratory environments. For vehicles to operate in realworld noisy and uncertain environments, they need to include numerous sensors and they need to include both reactive and deliberative features. The most effective software systems have been hierarchical or multi-layered. Many of these systems mimic biological systems. This paper reviews several software approaches for autonomous vehicles. While there are similarities, there are differences as well. Most of these software systems are very difficult to use, and few of them have the ability to learn. Autonomous vehicles promise remarkable capabilities for both civilian and military applications, but much work remains to develop intelligent systems software which can be used for a wide range of applications. In particular there is a need for reliable open-source software that can be used on inexpensive autonomous vehicles.

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“…Software agents have emerged as a suitable metaphor for interacting with computer processes that assist human decision making. Such software agents can reduce the amount of interaction between humans and the computer system and allow the humans to concentrate on other activities, such as assessing the situation, making decisions, or reacting to changes in the system [22]. In addition, such agents should not only retrieve information on request; but they should actively and intelligently anticipate, adapt and actively seek ways to support users [1; 19].…”

Section: The Moksaf Environmentmentioning

confidence: 99%

Varying the user interaction within multi-agent systems

Payne

Sycara

Lewis

2000

Proceedings of the Fourth International Conference on Autonomous Agents

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Agents within an open multi-agent system are located through their advertisements with middle agents. Such advertisements describe the agent's capability, ontology, query or task specification, and details about the data returned once the task has been completed. Agents may have similar capabilities, but exhibit different models of user interaction. A case study of a multi-agent system is described which contains a variety of different agents, some of which have functionally similar capabilities but involve different types of user interaction. We demonstrate how the choice of user interaction can have a significant effect on the performance of the whole agent community. This leads to the proposal that an agent's interactive style should also be included within its capability advertisement. General Terms

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Interface Agents in Complex Systems

Cited by 23 publications

References 9 publications

40 years of cognitive architectures: core cognitive abilities and practical applications

40 years of cognitive architectures: core cognitive abilities and practical applications

A Review of Intelligent Systems Software for Autonomous Vehicles

Varying the user interaction within multi-agent systems

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