Artificial Life Overview

Artificial Life (ALife) Overview

• ALife is a field devoted to understanding life by abstracting fundamental biological principles and recreating them in other media, like computers.
• This enables experimental manipulation and testing of these principles.
• ALife aims to study both life as we know it (on Earth) and alternative forms of life.
• ALife can be used for modelling the living and engineering solutions to known problems.

ALife in Short

• ALife focuses on creating synthetic behaviours similar to biological organisms in computers, mobile robots, and other systems.

ALife Goals

• Modelling: Understanding the living world by creating models that mimic its processes.
• Engineering: Applying ALife principles to solve real-world problems.

Illustrative Example

• Karl Sims' "blokies" (1994) is an example that examines morphology and neural control through evolution, alongside sensory inputs and evolutionary pressures to create self-propelling beings.

Big Questions in ALife (RQ's)

• Evolution of Complexity: Exploring the reasons behind the increasing complexity of life.
• Origins of Life: Understanding how pre-biotic systems, such as replicators, evolved.
• Major Transitions in Evolution: Examining significant changes in the evolution of life forms, such as the shift from prokaryotes to eukaryotes and the development of complex social structures
• Cultural-Biological Evolution Interactions: How cultural evolution impacts biological evolution and vice-versa.
• Fundamental Requirements for Intelligence: Identifying the core principles needed for intelligence.

Course Logistics

• Assessment: Includes a project, flash test, and reports based on exercises.
• Project: Groups of two. Free-themed projects relating to course topics and ALife or related areas.
• Project Details: Project proposals are due by October 24th, projects need to be completed and presentations given by January 23rd/26th.
• Flash test: 20 questions, 20 minutes.
• Reports: 5 reports of 2 pages each based on TP exercises, 10% of the grade.
• Contact Information: Given in the slides.

ALife Context

• ALife examines how life forms and environments interact, both natural and artificial.
• The natural world includes bio-organisms.
• The artificial world includes virtual reality, cellular automata, computer viruses, softbots (artificial beings).

Characteristics of Living Systems

• Autonomy: Independent functioning.
• Multiple Similar Components: Interacting similar parts create complex behaviour.
• Self-Organisation: Emergent complexity of structure within the system without external control.
• Local Control: Each component regulates itself within the system for example cells in tissue.
• Reproduction: Mechanisms for creating copies of life forms.
• Evolution: Adaptation to environmental pressures.
• Emergent Properties: Properties that arise from interactions within a system that cannot be predicted just from the components alone.

Parallels Between ALife and AI

• ALife is to life as AI is to intelligence.

ALife Pre-History

• Vaucanson's duck (~1730)

Near Ancestors of ALife

• Artificial neuron models (circa 1940)
• Turing's morphogenesis (circa 1950)
• Von Neumann's cellular automata (circa 1950)
• Grey Walter turtles (circa 1950)

Turtle Behavior

• Simple behaviours: Avoidance of obstacles, attraction to light sources.
• Complex results: Interplay with environment leads to complex behaviours.

ALife Workshop

• International workshop on Artificial Life, held in Los Alamos in 1987, organised by Christopher Langton (Santa Fe Institute). It brought together researchers in various domains with an interest in self-organized systems.

ALife's Continuance

• Numerous conferences and journals focusing on the topic.

ALife Versus AI

• ALife appears to be opposing to AI in terms of different approaches to solve problems. Behaviour vs solutions, dynamic evolution vs the final state. Parallel vs sequential approaches

Epistemology of Life

• Living Organism Components: Reproduction, Evolution, Phylogenetic, Ontogenetic, Epigenetic.
• Life as a Property: Von Neumann's self-reproduction model.
• Life and Non-life Distinction: Difficulty in defining the precise boundary between life and non-life.
• Definition of Life: Cells as the basis of life with self-maintenance and self-generation, consuming energy and nutrients.

Self-Organized Systems

• Components: Simple, emergent, system level, not existent at the component level.
• Examples: Temperature, pressure, turbulence, meteorology, economics, societies.
• Different from ALife: Includes phenomena outside of life but sharing self-organised principles.

Self-Organization Defining Principles

• No External Control: Internal processes drive system behaviours.
• Increase in Order: Systems move toward more complex and structured forms.
• Adaptability: Change and adjust in response to the environment.
• Interaction: Internal and external (environment) factors contribute to system behaviours.
• Asynchronism: No single control point in life as many processes happen at the same time but in different places.

Emergence

• Perceived Emergence: What emerges is in the eye of the beholder (or the modeler) – a syntactic emergence.
• True System Emergence: When a system develops new capabilities that existing models cannot explain, this is semantic emergence.
• Computational Systems Limit: Computational systems do not demonstrate emergence or exceed Turing machines.

Ways to Approach ALife

• Weak Position: ALife as a collection of models.
• Strong Position: ALife as a unifying paradigm for understanding various life forms.

Criticisms of ALife

• Overemphasis on rhetoric in early ALife research.
• Difficulty in carrying out scientific research in complex systems.

Granularity Comparison: Natural vs Artificial life

• Natural Life: subatomic particles, atoms, molecules, chemical interactions, organic molecules, cells, organs, and integrated organisms.
• Artificial Life: silicon technology, material technology, electronic interactions, integrated circuits, software hardware software, and electronics and mechanics.

Relationship between ALife and Other Fields

• Important connections: Evolutionary Algorithms, Physics, Complex Dynamic Systems, Immunology, Synthetic Chemistry, and Ethology.

Applications of ALife

• Modelling biological systems.
• Modelling socio-economic systems.
• Creating artificial organisms in simulated environments (e.g., Tierra, Prisoners’ Dilemma).
• Designing and building artificial life forms in real environments (e.g., mobile robots).
• Applying ALife principles to solve complex problems (e.g., grid computing).

Explore the fascinating field of Artificial Life (ALife), which seeks to understand life by replicating its fundamental principles in various media, including computers. This quiz will delve into the goals of ALife, such as modeling biological processes and engineering solutions. Gain insights into how synthetic behaviors can mirror biological organisms.