Expansionist/context-sensitive methodology: engineering of complex adaptive systems

Clymer, John R.

doi:10.1109/7.588485

Cited by 12 publications

(16 citation statements)

References 11 publications

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“…The following requirements [1,2,5] apply to any intelligent system described by a combined operational and decision making model of related, concurrent and sequential system processes.…”

Section: Intelligent System Requirementsmentioning

confidence: 99%

“…Bringing complex systems into being is difficult, and once the complexity of the system exceeds human comprehension the design and evaluation methodology must be automated. The multi-agent system design approach discussed above, and in [2], is one way to automate the search for an optimal system concept. This approach allows a set of related activities (processes) defining system capabilities and a set of mission goals to be understood and organized into a system concept of multiple agents collaborating to achieve multiple system goals.…”

Section: Multi-agent Coordination and Communication To Achieve Collabmentioning

confidence: 99%

“…Temporal reasoning requires a conceptual model of concurrent and sequential activities, representing their execution and interactions in time. The Theory of Context Sensitive Systems [1,2] provides the required basis for temporal reasoning.…”

Section: Temporal Reasoningmentioning

confidence: 99%

“…Collaboration among system agents is much more difficult to achieve than coordination; therefore, bringing such Complex Adaptive Systems (CAS) into being requires a systems engineering methodology [2] that uses simulation with Artificial Intelligence (AI):…”

mentioning

confidence: 99%

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Engineering of Intelligent, Complex Adaptive Systems Using an Agent‐based Architecture

Clymer¹

1997

INCOSE International Symp

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A methodology for bringing intelligent, Complex Adaptive Systems (CAS) into being is discussed, and the requirements for such intelligent systems are summarized. An agent-based system architecture is proposed that will satisfy the requirements for such an intelligent system. A facilitator agent that manages communication, coordination, and collaboration is proposed as a part of this architecture. A goal-directed behavior process is included as part of the facilitator agent to satisfy many of the intelligent system requirements. BRINGING COMPLEX SYSTEMS INTO BEINGAn agent is a collection of closely coupled concurrent processes that collaborate to perform a set of common functions or tasks. Agents are connected in a network and interact using a common agent communication language.

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“…The following requirements [1,2,5] apply to any intelligent system described by a combined operational and decision making model of related, concurrent and sequential system processes.…”

Section: Intelligent System Requirementsmentioning

confidence: 99%

Section: Multi-agent Coordination and Communication To Achieve Collabmentioning

confidence: 99%

Section: Temporal Reasoningmentioning

confidence: 99%

mentioning

confidence: 99%

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Engineering of Intelligent, Complex Adaptive Systems Using an Agent‐based Architecture

Clymer¹

1997

INCOSE International Symp

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“…This expansionist approach to system design [5] recognizes that the whole is greater than the sum of its parts and that the whole system must be designed properly so that its parts can effectively collaborate to solve the user/customer problem. How can a search of such a large and complex problem space be effectively performed?…”

mentioning

confidence: 99%

Optimization of Simulated System Effectiveness Using Evolutionary Algorithms

Clymer

1999

SIMULATION

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Using evolutionary algorithms, a search is performed based on a population where each population member consists of a vector of attribute values and a fitness value. A simulation of a system is run, given a particular set of the member attribute values, producing a fitness value. Fitness measures how well the system achieves its mission objectives. If the fitness has a random component, several runs are made to produce average fitness. The procedure is to select the best members from the population based on average fitness and mutate the member attribute values to produce new population members. Since population member attributes can affect process reaction times, wait logic, or decision logic, a search for the best attribute values over 50 to 100 generations can result in optimal fitness. In order to demonstrate the use of evolutionary algorithms in system optimization, a simple inventory system that has a complex fitness surface is considered.

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1.2.2 Engineering of Complex Adaptive Systems using OpEMCSS

Clymer

2000

INCOSE International Symp

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A graphical discrete event simulation library is proposed for the engineering of complex adaptive systems. This library works with EXTEND (Imagine That Inc), an inexpensive yet capable and easy to use simulation software package, and it is called Operational Evaluation Modeling for Context‐Sensitive Systems (OpEMCSS). Context‐Sensitive Systems (CSS) is a systems theory, based on finite state machines, that can assist a system designer in understanding and evaluating complex adaptive systems, represented as communicating concurrent (parallel) processes. CSS theory can be expressed using the OpEM graphical modeling language. Thus, OpEMCSS is a graphical simulation library that can model systems based on CSS theory and the OpEM language. As an example, an OpEMCSS model is discussed such that each of two intelligent agents learn rules that maximizes their average reward in the prisoner's dilemma game.

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Expansionist/context-sensitive methodology: engineering of complex adaptive systems

Cited by 12 publications

References 11 publications

Engineering of Intelligent, Complex Adaptive Systems Using an Agent‐based Architecture

Engineering of Intelligent, Complex Adaptive Systems Using an Agent‐based Architecture

Optimization of Simulated System Effectiveness Using Evolutionary Algorithms

1.2.2 Engineering of Complex Adaptive Systems using OpEMCSS

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