Elsevier

Theoretical Computer Science

Volume 192, Issue 2, 20 February 1998, Pages 315-351
Theoretical Computer Science

Contribution
Interactive foundations of computing

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Abstract

The claim that interactive systems have richer behavior than algorithms is surprisingly easy to prove. Turing machines cannot model interaction machines (which extend Turing machines with interactive input/output) because interaction is not expressible by a finite initial input string. Interaction machines extend the Chomsky hierarchy, are modeled by interaction grammars, and precisely capture fuzzy concepts like open systems and empirical computer science. Computable functions cannot model real-world behavior because functions are too strong an abstraction, sacrificing the ability to model time and other real-world properties to realize formal tractability.

Part I of this paper examines extensions to interactive models for algorithms, machines, grammars, and semantics, while Part II considers the expressiveness of different forms of interaction. Interactive identity machines are already more powerful than Turing machines, while noninteractive parallelism and distribution are algorithmic. The extension of Turing to interaction machines parallels that of the lambda to the pi calculus. Asynchronous and nonserializable interaction are shown to be more expressive than sequential interaction (multiple streams are more expressive than a single stream).

In Part III, it is shown that interaction machines cannot be described by sound and complete first-order logics (a form of Godel incompleteness), and that incompleteness is inherently necessary to realize greater expressiveness. In the final section the robustness of interactive models in expressing open systems, programming in the large, graphical user interfaces, and agent-oriented artificial intelligence is compared to the robustness of Turing machines. Less technical discussion of these ideas may be found in [25–27]. Applications of interactive models to coordination, objects and components, patterns and frameworks, software engineering, and AI are examined elsewhere [28,29].

The propositions P1-P36 embody the principal claims, while observations 01 through 040 provide additional insights.

Keywords

Turing machines
Interaction
Coordination
Time
On-line algorithms
Grammars
Process models
Games
Logic
Models
Incompleteness
Constraints
Emergent behavior
Empirical computer science

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