Bio-inspired Computing
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- Symbiotic Intelligence ... Bio-inspired Computing ... Neuroscience ... Connecting Brains ... Nanobots ... Molecular ... Neuromorphic ... Evolutionary/Genetic
- Collective Animal Intelligence ... Animal Ecology ... Animal Language ... Bird Identification
- History of Artificial Intelligence (AI) ... Creatives
- Lifelong Learning - Catastrophic Forgetting Challenge
- Other Challenges in Artificial Intelligence
- AI Solver ... Algorithms ... Administration ... Model Search ... Discriminative vs. Generative ... Optimizer ... Train, Validate, and Test
- Cybersecurity ... OSINT ... Frameworks ... References ... Offense ... NIST ... DHS ... Screening ... Law Enforcement ... Government ... Defense ... Lifecycle Integration ... Products ... Evaluating
- Sakana ... inspired by the way that fish and other animals work together in groups
- Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life | Albert-László Barabási - Amazon
- An AI Experiment Generated 40,000 Hypothetical Bioweapons in Just 6 Hours | David Nield - Science Alert
Bio-inspired Computing is a subset of metaphor-based metaheuristics
Bio-inspired AI or Nature-inspired AI is a branch of artificial intelligence that seeks to develop intelligent agents by mimicking the behavior of natural systems. This can include the behavior of animals, plants, or even entire ecosystems. Bio-inspired AI is a field of study that seeks to develop artificial intelligence (AI) systems by taking inspiration from biological systems. This can include the structure and function of biological organisms, as well as the principles of evolution and natural selection.
There are many different areas of bio-inspired AI, but some of the most common include:
- Artificial neural networks: are inspired by the structure and function of the human brain. They are made up of interconnected nodes that can learn to recognize patterns and make decisions.
- Genetic algorithms: are inspired by the process of natural selection. They use a technique called mutation to randomly change the parameters of an algorithm, and then select the best-performing algorithms to continue evolving.
- Evolutionary computation: is a broad term that encompasses a variety of techniques inspired by evolution, such as genetic algorithms, genetic programming, and differential evolution.
- Swarm intelligence: is inspired by the behavior of social insects, such as ants and bees. These insects are able to coordinate their actions to achieve complex tasks, such as building nests and foraging for food.
- Biomimetics: is the field of engineering that seeks to design artificial systems that mimic the function of biological systems. This can include the development of artificial limbs, organs, and sensors.
The world of AI has a lot of things around it to thank for its existence in our technological landscape of today. Not only have humans spent decades of research perfecting the mathematical calculations to make these wonderfully complex learning algorithms work but during this time we have looked further than our own species as inspiration to make the next generation of intelligent presence on our planet. Mother Nature, and all that it encompasses, has it’s roots firmly planted in the workings of Artificial Intelligence — and it’s here to stay. 5 Ways mother nature inspires artificial intelligence | Luke James - Towards Data Science
- Collective Animal Intelligence
- (Artificial) Immune System
- Biodegradability Prediction | Wikipedia
- Neuroscience - brain architecture - Cognitive Brain Function (Neurons) - Neural Network
- Cells
- Classical/Pavlov Conditioning - Reinforcement Learning (RL)
- Cuckoo Search | Wikipedia
- Epidemiology of Infectious Disease (networks) | L. Danon, A.P. Ford, T. House, C.P. Jewell, M. Keeling, G.O. Roberts, J.V. Ross, and M.C. Vernon
- Evolution Strategy | Wikipedia
- Excitable Media; forest fires, "the wave", heart conditions, axons | Wikipedia
- Firefly Algorithm | Wikipedia
- Fly Algorithm | Wikipedia
- {Leaping} Frog | R. Shivakumar, P.Tamilarasu and M.Panneerselvam
- Genetic Algorithm | Wikipedia - Survival of the Fittest/Evolution
- Grafting (decision trees) | Wikipedia
- (Artificial) Plant Optimization Algorithm | Wikipedia
- Plant Structures | Wikipedia
- Sensory Organs | Wikipedia