Biologically Inspired Artificial Intelligence Techniques

作者: Nistha Tandiya , Edward J. M. Colbert , Vuk Marojevic , Jeffrey H. Reed

DOI: 10.1007/978-3-319-77492-3_13

关键词: PopularityAdaptabilityArtificial immune systemTaxonomy (general)Anomaly detectionResilience (network)Robustness (computer science)Swarm intelligenceArtificial intelligenceComputer science

摘要: Recent years have seen continuous, rapid growth in popularity and capabilities of artificial intelligence, broadly speaking, other computational techniques inspired by biological analogies. It is most appropriate, therefore, for this book to explore how such might contribute enhancing cyber resilience. This chapter argues that the fast-paced development new cyber-related technologies complicates classical approach designing problem-specific algorithms Instead, “general-purpose” algorithms—such as biologically Intelligence (BIAI)—are more suited problems. BIAI allow learning, adaptability, robustness, which are compatible with resilience scenarios like self-organization, dynamic operation conditions, performance adversarial environment. introduces readers describes various their taxonomy. also proposes metrics can be used compare terms performance, implementation ease, requirements. Finally, illustrates potential via several case studies—applications pertaining wireless communication systems.

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