Abstract
The absence of powerful control structures and processes that synchronize, coordinate, switch between, choose among, regulate, direct, modulate interactions between, and combine distinct yet interdependent modules of large connectionist networks (CN) is probably one of the most important reasons why such networks have not yet succeeded at handling difficult tasks (e.g. complex object recognition and description, complex problem-solving, planning). This paper examines how CN built from large numbers of relatively simple neuronlike units can be given the ability to handle problems that in typical multicomputer networks and artificial intelligence programs-along with all other types of programs-are always handled using extremely elaborate and precisely worked out central control (coordination, synchronization, switching, etc.). The paper shows the several mechanisms for central control of this un-brain-like sort that CN already have built into them-albeit in hidden, often overlooked, ways. The kinds of control mechanisms found in computers, programs, fetal development, cellular function and the immune system, evolution, social organizations, and especially brains, that might be of use in CN are examined. Particularly intriguing suggestions are found in the pacemakers, oscillators, and other local sources of the brain’s complex partial synchronies; the diffuse, global effects of slow electrical waves and neurohormones; the developmental program that guides fetal development; communication and coordination within and among living cells; the working of the immune system; the evolutionary processes that operate on large populations of organisms; and the great variety of partially competing partially cooperating controls found in small groups, organizations, and larger societies. All these systems are rich in control-but typically control that emerges from complex interactions of many local and diffuse sources. This paper explores how several different kinds of plausible control mechanisms might be incorporated into CN, and assesses their potential benefits with respect to their cost.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1-2 |
| Number of pages | 2 |
| Journal | Journal of Experimental and Theoretical Artificial Intelligence |
| Volume | 2 |
| Issue number | 4 |
| DOIs | |
| State | Published - Jan 1 1990 |
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All Science Journal Classification (ASJC) codes
- Software
- Theoretical Computer Science
- Artificial Intelligence
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Coordination and control structures and processes : Possibilities for connectionist networks (cn). / Honavar, Vasant; Uhr, Leonard.
In: Journal of Experimental and Theoretical Artificial Intelligence, Vol. 2, No. 4, 01.01.1990, p. 1-2.Research output: Contribution to journal › Article
TY - JOUR
T1 - Coordination and control structures and processes
T2 - Possibilities for connectionist networks (cn)
AU - Honavar, Vasant
AU - Uhr, Leonard
PY - 1990/1/1
Y1 - 1990/1/1
N2 - The absence of powerful control structures and processes that synchronize, coordinate, switch between, choose among, regulate, direct, modulate interactions between, and combine distinct yet interdependent modules of large connectionist networks (CN) is probably one of the most important reasons why such networks have not yet succeeded at handling difficult tasks (e.g. complex object recognition and description, complex problem-solving, planning). This paper examines how CN built from large numbers of relatively simple neuronlike units can be given the ability to handle problems that in typical multicomputer networks and artificial intelligence programs-along with all other types of programs-are always handled using extremely elaborate and precisely worked out central control (coordination, synchronization, switching, etc.). The paper shows the several mechanisms for central control of this un-brain-like sort that CN already have built into them-albeit in hidden, often overlooked, ways. The kinds of control mechanisms found in computers, programs, fetal development, cellular function and the immune system, evolution, social organizations, and especially brains, that might be of use in CN are examined. Particularly intriguing suggestions are found in the pacemakers, oscillators, and other local sources of the brain’s complex partial synchronies; the diffuse, global effects of slow electrical waves and neurohormones; the developmental program that guides fetal development; communication and coordination within and among living cells; the working of the immune system; the evolutionary processes that operate on large populations of organisms; and the great variety of partially competing partially cooperating controls found in small groups, organizations, and larger societies. All these systems are rich in control-but typically control that emerges from complex interactions of many local and diffuse sources. This paper explores how several different kinds of plausible control mechanisms might be incorporated into CN, and assesses their potential benefits with respect to their cost.
AB - The absence of powerful control structures and processes that synchronize, coordinate, switch between, choose among, regulate, direct, modulate interactions between, and combine distinct yet interdependent modules of large connectionist networks (CN) is probably one of the most important reasons why such networks have not yet succeeded at handling difficult tasks (e.g. complex object recognition and description, complex problem-solving, planning). This paper examines how CN built from large numbers of relatively simple neuronlike units can be given the ability to handle problems that in typical multicomputer networks and artificial intelligence programs-along with all other types of programs-are always handled using extremely elaborate and precisely worked out central control (coordination, synchronization, switching, etc.). The paper shows the several mechanisms for central control of this un-brain-like sort that CN already have built into them-albeit in hidden, often overlooked, ways. The kinds of control mechanisms found in computers, programs, fetal development, cellular function and the immune system, evolution, social organizations, and especially brains, that might be of use in CN are examined. Particularly intriguing suggestions are found in the pacemakers, oscillators, and other local sources of the brain’s complex partial synchronies; the diffuse, global effects of slow electrical waves and neurohormones; the developmental program that guides fetal development; communication and coordination within and among living cells; the working of the immune system; the evolutionary processes that operate on large populations of organisms; and the great variety of partially competing partially cooperating controls found in small groups, organizations, and larger societies. All these systems are rich in control-but typically control that emerges from complex interactions of many local and diffuse sources. This paper explores how several different kinds of plausible control mechanisms might be incorporated into CN, and assesses their potential benefits with respect to their cost.
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UR - http://www.scopus.com/inward/citedby.url?scp=84951578676&partnerID=8YFLogxK
U2 - 10.1080/09528139008953727
DO - 10.1080/09528139008953727
M3 - Article
AN - SCOPUS:84951578676
VL - 2
SP - 1
EP - 2
JO - Journal of Experimental and Theoretical Artificial Intelligence
JF - Journal of Experimental and Theoretical Artificial Intelligence
SN - 0952-813X
IS - 4
ER -