Artificial intelligence-definition and practice

Simmons, A.B.; Chappell, S.G.

doi:10.1109/48.551

Cited by 55 publications

(26 citation statements)

References 25 publications

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“…These properties of the task suggest a time-ordered architecture (TOA) (cf. also Simmons and Chappell [24], and Crowley [4]). See The TOA is a multiple-loop mechanism in which control problems are partitioned into classes based on required response time and information abstraction.…”

Section: Architecture Componentsmentioning

confidence: 94%

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A time-ordered architecture for integrating reflexive and deliberative behavior

Lewis¹

1991

SIGART Bull.

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The objective of our research is to establish a universal architecture for effecting an autonomous control logic for land, space, air, and underwater platforms. Although the operational constraints of each platform are diverse, we perceive the general task to be the execution of a mission in an unstructured environment. The task requires reflexive and deliberative mechanisms that sometime trade off problems and sometime combine to solve a single problem. We propose a hierarchical time-ordered architecture for integrating these mechanisms. Integration RequirementsAssume that a platform is unmanned and incapable of communication with an external agent. The platform is equipped with a sensor suite, an effector suite, a mission, and (optionally) a priori information about itself and the environment in which it is operating. The task is to respond appropriately to unanticipated events. Unanticipated events refer to environmental and platform anomalies which are unplanned, e.g. the appearance of an unexpected obstacle, the mechanical failure of a piece of hardware, or the inability to control vehicle dynamics within a predetermined range.Typical categories of responses are do nothing, modify mission, or abort mission. The components of the task that require integration are reflexive behavior (RB) and deliberative behavior (DB). For example, suppose a platform has planned a path to a goal (DB) and comes upon an unexpected object. If time permits, the platform should replan a path around the obstacle and proceed to the goal (DB). If time does not permit replanning of a path, the platform should stray from the object (RB) and place itself in position to replan a path to the goal (DB). A third course of action is to stray from the object and replan a path to the goal simultaneously (RB/DB). Other examples of behavior that require both RB and DB are discussed in Georgeff and Lansky [10], Schoppers [23], and Dean and Boddy [5]. The goal of our research is to understand how RB and DB trade off problems, how they combine to solve a single problem, and how decisions for one or the other evolve in dynamic environments. Architecture ComponentsThe distinction between RB and DB is grounded in (i) the time available to respond to an event, (ii) information abstraction, and (iii) the ability to project into the future. Essentially, DB requires more time, more abstract knowledge, and more ability to think about the future than RB. These properties of the task suggest a time-ordered architecture (TOA) (cf. also Simmons and Chappell [24], and Crowley [4]). See Figure 1. z < COORDINATION y SENSORS EFFECTORS rn 0 O N Z Figure 1: The Time-Ordered Architecture (adapted from Hebert et al [12], page 2)The TOA is a multiple-loop mechanism in which control problems are partitioned into classes based on required response time and information abstraction. Each class of problems resides on a single level of the TOA, and a problemsolving technique on a single level operates on a uniform abstraction of data (e.g. signals, signs, or symbols). RB emer...

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Section: Architecture Componentsmentioning

confidence: 94%

“…Our approach to the integration of deliberative and reflexive behavior is much like that taken by Simmons and Chappell [24], Crowley [4], and Gat [this issue].…”

Section: Comparison To Other Systemsmentioning

confidence: 99%

A time-ordered architecture for integrating reflexive and deliberative behavior

Lewis¹

1991

SIGART Bull.

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“…An intelligent agent incorporates the skills required to pass the Turing Test, which assesses whether a machine can think like a human? [2,3]. So an intelligent agent should be skilled in perception, practical reasoning and have an ability to take action to achieve its goals.…”

Section: Intelligent Agentmentioning

confidence: 99%

“…However, the concept of AI is not new and can be traced back to Ramon Llull's theory of a reasoning machine in 1300 CE and even Aristotle's syllogisms in 300 BC [1,2]. However, it is only since the 1950s, clearer definitions and practical applications have been formulated [3,4]. While there was a lull in the development of AI in the 70s and 80s because of loss of interest and funding, there has been in the most recent period a dramatic revival in the research and development of AI programs.…”

Section: Introductionmentioning

confidence: 99%

Use of Artificial Intelligence in Healthcare Delivery

Reddy¹

2018

eHealth - Making Health Care Smarter

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In recent years, there has been an amplified focus on the use of artificial intelligence (AI) in various domains to resolve complex issues. Likewise, the adoption of artificial intelligence (AI) in healthcare is growing while radically changing the face of healthcare delivery. AI is being employed in a myriad of settings including hospitals, clinical laboratories, and research facilities. AI approaches employing machines to sense and comprehend data like humans has opened up previously unavailable or unrecognised opportunities for clinical practitioners and health service organisations. Some examples include utilising AI approaches to analyse unstructured data such as photos, videos, physician notes to enable clinical decision making; use of intelligence interfaces to enhance patient engagement and compliance with treatment; and predictive modelling to manage patient flow and hospital capacity/resource allocation. Yet, there is an incomplete understanding of AI and even confusion as to what it is? Also, it is not completely clear what the implications are in using AI generally and in particular for clinicians? This chapter aims to cover these topics and also introduce the reader to the concept of AI, the theories behind AI programming and the various applications of AI in the medical domain.

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“…The properties that distinguish RB and D B suggest a hierarchical time-ordered architecture (TOA) (Simmons and Chappell [27], Crowley [8]). See Kaelbling and Rosenschein I201), reactive action packages (Firby [12]), or associative networks.…”

Section: An Authentic Dai Problem: Distributed Controlmentioning

confidence: 99%

Dimensions And Heuristics For The Design Of Distributed Artificial Intelligence Architectures

Lewis¹,

Gwin²

OCEANS 91 Proceedings

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Our objective in the paper is to establish a framework f o r thinking about problems whose solutions require multiple agents working together. Particularly, we are concerned with agents who operate in an undersea environment. We discuss three problems within this framework: ( i ) semi-automated platform command and control, (ii) fully-automated control of autonomous underwater vehicles (AUVs), and (iii) joint platformlAUV mission control. Our work proceeds under the hypothesis that each problem is a Distributed Artificial Intelligence ( D A I ) problem and that each problem is essentially isomorphic. In the paper we characterize the concept of DAI problem, propose a table of dimensions for casting DAI problems, discuss several DAI design heuristics, and describe our work on the three problems above.

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Artificial intelligence-definition and practice

Cited by 55 publications

References 25 publications

A time-ordered architecture for integrating reflexive and deliberative behavior

A time-ordered architecture for integrating reflexive and deliberative behavior

Use of Artificial Intelligence in Healthcare Delivery

Dimensions And Heuristics For The Design Of Distributed Artificial Intelligence Architectures

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