Difference between revisions of "Bio-inspired Computing"

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* [[Lifelong Learning]] - Catastrophic Forgetting Challenge
 
* [[Lifelong Learning]] - Catastrophic Forgetting Challenge
 
* [[Other Challenges]] in Artificial Intelligence
 
* [[Other Challenges]] in Artificial Intelligence
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* [[AI Solver]] ... [[Algorithms]] ... [[Algorithm Administration|Administration]] ... [[Model Search]] ... [[Discriminative vs. Generative]] ... [[Optimizer]] ... [[Train, Validate, and Test]]
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* [[AI Solver]] ... [[Algorithms]] ... [[Algorithm Administration|Administration]] ... [[Model Search]] ... [[Discriminative vs. Generative]] ... [[Train, Validate, and Test]]
 
* [[Cybersecurity]] ... [[Open-Source Intelligence - OSINT |OSINT]] ... [[Cybersecurity Frameworks, Architectures & Roadmaps | Frameworks]] ... [[Cybersecurity References|References]] ... [[Offense - Adversarial Threats/Attacks| Offense]] ... [[National Institute of Standards and Technology (NIST)|NIST]] ... [[U.S. Department of Homeland Security (DHS)| DHS]] ... [[Screening; Passenger, Luggage, & Cargo|Screening]] ... [[Law Enforcement]] ... [[Government Services|Government]] ... [[Defense]] ... [[Joint Capabilities Integration and Development System (JCIDS)#Cybersecurity & Acquisition Lifecycle Integration| Lifecycle Integration]] ... [[Cybersecurity Companies/Products|Products]] ... [[Cybersecurity: Evaluating & Selling|Evaluating]]
 
* [[Cybersecurity]] ... [[Open-Source Intelligence - OSINT |OSINT]] ... [[Cybersecurity Frameworks, Architectures & Roadmaps | Frameworks]] ... [[Cybersecurity References|References]] ... [[Offense - Adversarial Threats/Attacks| Offense]] ... [[National Institute of Standards and Technology (NIST)|NIST]] ... [[U.S. Department of Homeland Security (DHS)| DHS]] ... [[Screening; Passenger, Luggage, & Cargo|Screening]] ... [[Law Enforcement]] ... [[Government Services|Government]] ... [[Defense]] ... [[Joint Capabilities Integration and Development System (JCIDS)#Cybersecurity & Acquisition Lifecycle Integration| Lifecycle Integration]] ... [[Cybersecurity Companies/Products|Products]] ... [[Cybersecurity: Evaluating & Selling|Evaluating]]
 
* [[Sakana]] ... inspired by the way that fish and other animals work together in groups
 
* [[Sakana]] ... inspired by the way that fish and other animals work together in groups

Revision as of 21:56, 5 March 2024

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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






Biological and Artificial Intelligence

Explores the evolution of human intelligence and its implications for AI. The book identifies the five major breakthroughs in the history of the brain that gave rise to our cognitive abilities. They are:

  • The emergence of neurons**. About a billion years ago, the first cells with specialized functions for communication and computation appeared, forming the basis of nervous systems.
  • The development of the cortex**. About 500 million years ago, the first vertebrates evolved a thin layer of tissue around their brains, called the cortex, that enabled complex sensory processing and motor control.
  • The expansion of the cortex**. About 200 million years ago, the cortex of mammals began to grow larger and more folded, creating more surface area and connections for higher cognitive functions such as memory, learning, and planning.
  • The specialization of the cortex**. About 100 million years ago, the cortex of primates became more differentiated into distinct regions, each with specialized roles for vision, language, social cognition, and other abilities.
  • The integration of the cortex**. About 2 million years ago, the cortex of hominins (our ancestors) developed a dense network of long-range connections, called the default mode network, that enabled self-awareness, creativity, and mental simulation.



Embodied Minds and Cognitive Agents

Discuss embodied minds, his research into limb regeneration and collective intelligence, cognitive light cones, and much more. Dr. Levin and the Levin Lab work at the intersection of biology, artificial life, bioengineering, synthetic morphology, and cognitive science. Embodied Minds and Cognitive Agents refer to two interconnected concepts:

1. Embodied Minds:

This theory argues that cognition is not solely confined to the brain, but is deeply influenced by the body and its interactions with the environment. It challenges the traditional Cartesian view of mind-body dualism, which separated mental processes from physical embodiment.

Embodied cognition emphasizes how factors like:

  • Body structure and sensory systems: Our physical form shapes how we perceive and interact with the world. For example, our two eyes give us depth perception, and our hands allow us to manipulate objects.
  • Motor skills and actions: Our ability to move and interact with the environment influences our thinking and learning. For example, practicing a sport can improve cognitive skills like focus and decision-making.
  • Emotions and bodily states: Our emotional state and physical sensations can impact our thoughts and judgments. For example, feeling tired can make it harder to concentrate.


2. Cognitive Agents:

These are artificial systems that exhibit some degree of intelligent behavior. They can be implemented in various forms, including robots, software programs, and virtual avatars. Cognitive agents often incorporate principles of embodied cognition to:

  • Perceive and interact with their environment: This can involve using sensors, cameras, and other tools to gather information and respond to stimuli.
  • Learn and adapt: Cognitive agents may employ various machine learning techniques to improve their performance over time and adapt to new situations.
  • Interact with humans in a meaningful way: This can involve understanding human language, emotions, and social cues, and responding in a way that is perceived as intelligent and engaging.

The connection between these concepts lies in the fact that understanding how embodiment impacts human cognition can inform the design and development of more sophisticated and effective cognitive agents. By building artificial systems that take into account the physical and environmental factors that influence intelligence, we can create agents that are better able to understand the world and interact with it in a meaningful way.


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