An artificial immune system approach to automated program verification: Towards a theory of undecidability in biological computing

10.7287/peerj.preprints.2690v2 ◽

2017 ◽

Author(s):

Soumya Banerjee

Keyword(s):

Immune System ◽

System Approach ◽

Artificial Immune System ◽

Program Verification ◽

Verification Task ◽

Artificial Immune ◽

Biological Computing ◽

Robust Computation ◽

Invariant Shape ◽

Program Invariants

An immune system inspired Artificial Immune System (AIS) algorithm is presented, and is used for the purposes of automated program verification. Relevant immunological concepts are discussed and the field of AIS is briefly reviewed. It is proposed to use this AIS algorithm for a specific automated program verification task: that of predicting shape of program invariants. It is shown that the algorithm correctly predicts program invariant shape for a variety of benchmarked programs. Program invariants encapsulate the computability of a particular program, e.g. whether it performs a particular function correctly and whether it terminates or not. This work also lays the foundation for applying concepts of theoretical incomputability and undecidability to biological systems like the immune system that perform robust computation to eliminate pathogens.

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An artificial immune system approach to automated program verification: Towards a theory of undecidability in biological computing

10.7287/peerj.preprints.2690v1 ◽

2017 ◽

Author(s):

Soumya Banerjee

Keyword(s):

Immune System ◽

System Approach ◽

Artificial Immune System ◽

Program Verification ◽

Verification Task ◽

Artificial Immune ◽

Biological Computing ◽

Robust Computation ◽

Invariant Shape ◽

Program Invariants

An immune system inspired Artificial Immune System (AIS) algorithm is presented, and is used for the purposes of automated program verification. Relevant immunological concepts are discussed and the field of AIS is briefly reviewed. It is proposed to use this AIS algorithm for a specific automated program verification task: that of predicting shape of program invariants. It is shown that the algorithm correctly predicts program invariant shape for a variety of benchmarked programs. Program invariants encapsulate the computability of a particular program, e.g. whether it performs a particular function correctly and whether it terminates or not. This work also lays the foundation for applying concepts of theoretical incomputability and undecidability to biological systems like the immune system that perform robust computation to eliminate pathogens.

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An artificial immune system approach to automated program verification: Towards a theory of undecidability in biological computing

10.7287/peerj.preprints.2690v3 ◽

2017 ◽

Cited By ~ 1

Author(s):

Soumya Banerjee

Keyword(s):

Immune System ◽

System Approach ◽

Artificial Immune System ◽

Program Verification ◽

Verification Task ◽

Artificial Immune ◽

Biological Computing ◽

Robust Computation ◽

Invariant Shape ◽

Program Invariants

An immune system inspired Artificial Immune System (AIS) algorithm is presented, and is used for the purposes of automated program verification. Relevant immunological concepts are discussed and the field of AIS is briefly reviewed. It is proposed to use this AIS algorithm for a specific automated program verification task: that of predicting shape of program invariants. It is shown that the algorithm correctly predicts program invariant shape for a variety of benchmarked programs. Program invariants encapsulate the computability of a particular program, e.g. whether it performs a particular function correctly and whether it terminates or not. This work also lays the foundation for applying concepts of theoretical incomputability and undecidability to biological systems like the immune system that perform robust computation to eliminate pathogens.

Download Full-text

An Artificial Immune System Approach to Automated Program Verification: Towards a Theory of Undecidability in Biological Computing

Interdisciplinary Description of Complex Systems ◽

10.7906/indecs.19.4.3 ◽

2021 ◽

Vol 19 (4) ◽

pp. 493-501

Author(s):

Soumya Banerjee

Keyword(s):

Immune System ◽

System Approach ◽

Artificial Immune System ◽

Program Verification ◽

Artificial Immune ◽

Biological Computing

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Transport modeling: An artificial immune system approach

Yugoslav journal of operations research ◽

10.2298/yjor0601003t ◽

2006 ◽

Vol 16 (1) ◽

pp. 3-30

Author(s):

Dusan Teodorovic ◽

Jovan Popovic ◽

Panta Lucic

Keyword(s):

Immune System ◽

Real Time ◽

Traffic Control ◽

System Approach ◽

Artificial Immune System ◽

Control Strategies ◽

Transportation Systems ◽

Artificial Immune ◽

Real Time Traffic ◽

Wide Range

This paper describes an artificial immune system approach (AIS) to modeling time-dependent (dynamic, real time) transportation phenomenon characterized by uncertainty. The basic idea behind this research is to develop the Artificial Immune System, which generates a set of antibodies (decisions, control actions) that altogether can successfully cover a wide range of potential situations. The proposed artificial immune system develops antibodies (the best control strategies) for different antigens (different traffic "scenarios"). This task is performed using some of the optimization or heuristics techniques. Then a set of antibodies is combined to create Artificial Immune System. The developed Artificial Immune transportation systems are able to generalize, adapt, and learn based on new knowledge and new information. Applications of the systems are considered for airline yield management, the stochastic vehicle routing, and real-time traffic control at the isolated intersection. The preliminary research results are very promising.

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