Artificial Life - An Overview

1. Artificial Life - An Overview Ritendra Datta Penn State University

2. What is Life? • State of a functional activity and continual change, before death (defined complimentarily as end-of-life). • Characterized by the capability to: • Reproduce itself, • Adapt to an environment in a quest for survival, and • Take Actions independent of exterior agents.

3. Nature as a special case of Life • The Biology of Nature so far been the scientific study of life on Earth based on Carbon-chain chemistry. • However, nothing restricts the study of properties of life to carbon-chain chemistry; it is merely the only form of life so far available for study. • Further motivation to study life as a generic concept comes from the hypothesis that we are perhaps just one possible atom combination that makes this life possible. We haven’t met other examples (Aliens).

4. …which brings us to A-Life • Lack of any available non-carbon based life-forms motivates us to create an artificial environment and a set of rules for life to evolve. • Artificial Life, or ALife or AL is the study of non-organic organisms, beyond the creations of nature, that possess the essential properties of life as we understand it, and whose environment is artificially created in an alternative media, which very often is a logical device like the computer.

5. ALife as a Synthesis approach • Rather than being an analytical study of “natural” life, A-Life is a Synthesis approach to studying any form of Life. • We have : • an artificially-created environment (usually) within computers, • A fairly universal set of rules and properties of life, derived from the one example we have of life - Naturallife.

6. So what is the motivation? • A-Life could have been dubbed as yet-another-approach to studying intelligent life, had it not been for the Emergent propertiesin life that motivates scientists to explore the possibility of artificially creating life and expecting the unexpected. • An Emergent property is created when something becomes more than sum of its parts. For example, half a human is not capable of working without the other half, but together, capable of very complex behavior (not a representative example).

7. So where does A-Life fit in? • The A-Life concept helps to: • Study existing natural life forms by trying to simulate the generic rules they follow, the environmental parameters like entropy/chaos , and the seed, i.e. the initial set of elements on which the rules of life apply under the given environmental condition, in order to understand evolution in nature. • Create new life within the digital world by creating new set of external parameters, seeds, and rules of evolution, and let lifefind a way.

8. So is A-Life = AI ??

9. A-Life : Emergence • What you get when something is more than the sum of its parts. • Human thoughts rely on nearly all cells that make up the brain - single cells are incapable of thought - thought is the emergence property of these cells coming together and interacting to give complex results - motivation behind CA, NN. • Extreme example: Earth as a one living thing, consisting of whole of nature being in dynamic equilibrium, each part having baring on the other.

10. A-Life : Entropy • Second Law of Thermodynamics : When two systems are joined together, the entropy (or chaos) in the combined system is greater than the sum of the individual systems. • This roughly applies to all systems, including those that exchange information. • Life is all about fighting against entropy : as other systems lose information to surroundings, life not only keeps hold of its information, but also increases its amount of information.

11. A-Life : Complexity • Life is a complex system : It is a dynamic system that can keep on changing and evolving over a great period of time withoutdying. • If the amount of information exchange in a system is varied from low to high, it gives Fixed, Periodic, and Chaotic systems in that order. Somewhere in between, a system exhibits complex behavior. • Accordingly, each unit in a system either dies, freezes, pulsates, or behaves in a complex manner.

12. A-Life : Chaos Theory • Chaos Theory explains apparent randomness - many apparently random events are not truly random - they are just iteration of simple rules on existing states (and possibly previous states) generating complex behavior - they live on the edge of total chaos. • Most natural processes are chaotic - sea, wind. • Some man-made processes are chaotic - Financial market. • Lack of knowledge of all rules,inputs and seed prevents us from determining the exact state of such a system at a point, but knowledge of some of those dominant rules/inputs lead to possible prediction of general behavior of the system. • This lack of knowledge of all parameters leads us to conclude it to be random behavior of the system.

13. A-Life : Current research areas • Mathematical, Philosophical, Biological foundations, Social and Ethical implications of A-Life. • Cellular Automata • Neural Networks • Genetic Algorithms • Origin, Self-organization, Repair and Replication • Evolutionary / Adaptive Dynamics • Autonomous,Adaptive and Evolving Robots • Software Agents (good/evil) • Emergent Collective Behaviors, Swarms. • Synthetic/Artificial Chemistry/Biology/Materials • Applications: Finance, Economics, Gaming, MEMS etc

14. ALife:Foundation/Implications • Research on Foundationtries to answer questions about the motivation behind such a ground-breaking concept, using our existing knowledge base in Math, Chemistry, Biology, Philosophy of life etc. The Question is “How, why and where can the ALife approach succeed (or fail)?” • Research on Implicationstries to understand and explain how the extension of life as a generic concept impacts our understanding of the very basics of natural life, shattering (or possibly not affecting) many-a-belief about God, creation and destruction. The Question here is “How does ALife fit in (if at all) to the present-day social setup of morals and ethics, often laid out by the various religious texts ?”

15. Alife : Cellular Automata • Inspired by the way Natural biological cells behave and interact with their neighboring cells by following rules set out by the DNA code in them. • Cellular Automata (CA) is an array of N-dimensional ‘cells’ that interact with their neighboring cells according to a pre-determined set of rules, to generate actions, which in turn may trigger a new series of reactions on itself or its neighbors. • The best known example is Conway’s Life, which is a 2-state2-D CA with simple rules (see on right) applied to all cells simultaneously to create generations of cells from an initial pattern. • Different initial patterns generate different behavorial patterns, some die away (unstable), some blink (periodic), and the rest show complexbehavior by continuing to live and evolve.