A situated view of representation and control

Rosenschein, Stanley J.; Kaelbling, Leslie Pack

doi:10.1016/0004-3702(94)00056-7

Cited by 125 publications

(29 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our approach has some similarities with the situated automata work of Rosenschein and Kaelbling (1995). Rosenschein and Kaelbling model an agent using two functions, a state update function, f , which maps the input (percepts) and the value of the agent's internal state at the last cycle into a new value of the internal state, and an output function, g, that maps the input and the value of the agent's internal state at the last cycle into the output (actions).…”

Section: Related Workmentioning

confidence: 99%

“…Following, for example Rosenschein and Kaelbling (1995), we assume that the agent's state consists of finitely many 'memory locations' l 1 ,. .…”

Section: The Agent-environment Modelmentioning

confidence: 99%

“…In what follows we view the agent and its environment as a pair of interacting automata (cf (Rosenschein and Kaelbling, 1995)) performing a sense-thinkact cycle (see Figure 1). At each cycle, the environment generates an input or 'percept' to the agent (updating several locations in the agent's memory), followed by the agent generating an output or 'action' to the environment.…”

Section: A Simple Agent-environment Systemmentioning

confidence: 99%

See 2 more Smart Citations

A Logic of Situated Resource-Bounded Agents

Alechina

Logan

2008

J of Log Lang and Inf

View full text Add to dashboard Cite

Abstract. We propose a framework for modelling situated resource-bounded agents. The framework is based on an objective ascription of intentional modalities and can be easily tailored to the system we want to model and the properties we wish to specify. As an elaboration of the framework, we introduce a logic, OBA, for describing the observations, beliefs, goals and actions of simple agents, and show that OBA is complete, decidable and has an efficient model checking procedure, allowing properties of agents specified in OBA to be verified using standard theorem proving or model checking techniques.

show abstract

Section: Related Workmentioning

confidence: 99%

“…Following, for example Rosenschein and Kaelbling (1995), we assume that the agent's state consists of finitely many 'memory locations' l 1 ,. .…”

Section: The Agent-environment Modelmentioning

confidence: 99%

Section: A Simple Agent-environment Systemmentioning

confidence: 99%

See 1 more Smart Citation

A Logic of Situated Resource-Bounded Agents

Alechina

Logan

2008

J of Log Lang and Inf

View full text Add to dashboard Cite

show abstract

“…The difference is rather like the distinction between interpreted and compiled programming languages. The best-known example of this work is the situated automata paradigm of Leslie Kaelbling and Stanley Rosenschein [48]. A review of the role of logic in intelligent agents may be found in [54].…”

Section: End Function Actionmentioning

confidence: 99%

“…-the agent network architecture developed by Pattie Maes [32,34,35]; -Nilsson's teleo reactive programs [40]; -Rosenchein and Kaelbling's situated automata approach, which is particularly interesting in that it shows how agents can be specified in an abstract, logical framework, and compiled into equivalent, but computationally very simple machines [47,28,27,48]; -Agre and Chapman's pengi system [1]; -Schoppers' universal plans -which are essentially decision trees that can be used to efficiently determine an appropriate action in any situation [52]; -Firby's reactive action packages [17].…”

Section: The Objective Is To Explore a Distant Planet More Concretelmentioning

confidence: 99%

Intelligent Agents: The Key Concepts

Wooldridge

2002

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Abstract. This chapter aims to introduce the reader to the basic issues surrounding the design and implementation of intelligent agents. It begins by motivating the idea of an agent, presents a definition of agents and intelligent agents. The article then goes on to discuss four major approaches to building agents. First, logic based architectures are reviewed, in which decision-making is viewed as logical deduction. Second, reactive architectures are discussed, in which symbolic representations and models are eschewed in favour of a closer relationship between agent perception and action. Third, we discuss belief-desire-intention architectures, in which decision making is viewed as practical reasoning from beliefs about how the world is and will be to the options available to an agent, and finally to intentions and actions. Fourth, we review layered agent architectures, in which decision making is partitioned into a number of different decision making layers, each dealing with the agent's environment at a different level of abstraction.

show abstract