0000000000437375
AUTHOR
Orazio Miglino
Artificial organisms as tools for the development of psychological theory: Tolman's lesson
In the 1930s and 1940s, Edward Tolman developed a psychological theory of spatial orientation in rats and humans. He expressed his theory as an automaton (the ‘‘schematic sowbug’’) or what today we would call an ‘‘artificial organism.’’ With the technology of the day, he could not implement his model. Nonetheless, he used it to develop empirical predictions which tested with animals in the laboratory. This way of proceeding was in line with scientific practice dating back to Galileo. The way psychologists use artificial organisms in their work today breaks with this tradition. Modern ‘‘artificial organisms’’ are constructed a posteriori, working from experimental or ethological observations…
Breedbot: An Edutainment Robotics System to Link Digital and Real World
The paper describes Breedbot an edutainment software and hardware system that could be used to evolve autonomous agents in digital (software) world and to transfer the evolved minds in physical agents (robots). The system is based on a wide variety of Artificial Life techniques (Artificial Neural Networks, Genetic Algorithms, User Guided Evolutionary Design and Evolutionary Robotics). An user without any computer programming skill can determine the robot behaviour. Breedbot was used as a didactic tool in teaching Evolutionary Biology and as a futuristic toy by several Science Centers. The digital side of Breedbot is downloadable from www.isl.unina.it/breedbot.
Replicating Experiments in “Detour Behavior” with Artificially Evolved Robots: An A-Life Approach to Comparative Psychology
To be useful in psychology "artificial organisms" have to perform tasks comparable to those performed by animals. One way to achieve this is to rephcate actual animal experiments. Here we reproduce an experiment showing "detour behavior" in chicks - a behavior usually explained in terms of "cognitive maps" or other forms of internal representation. We artificially evolve software-simulated robots with a "generic" ability to detour. Sensor-motor physics are carefully calibrated with data from a physical robot. Robot architecture is constrained to exclude internal representation. The evolutionary process rewards exploratory skills as well as detour behavior. Robot performance matches the resu…
TeamSim: An Educational Micro-World for the Teaching of Team Dynamics
In this paper we present an educational micro-world in which a learner can manipulate variables affecting the efficiency with which a team adapts to its environment. These include the structure of hierarchical relations within the team, the structure of the communications network, and other environmental parameters. Using the micro-world, the learner can design experiments (simulations) exploring notions in the dynamics of small groups. A freeware version of TeamSim is available from http:// laral.istc.cnr.it/gigliotta/.
A “Noise Gene” for Econets
Genetically controlled noise is applied to the weights of neural networks trained with a genetic algorithm. Networks simulate simple organisms living in an environment Reproduction is based on the ability of each network, during its life, to respond to sensory information from the environment with appropriate motor action. Each network has an amount of noise which is genetically inherited (in the ‘noise gene’) with mutations and it varies interindividually. Noise modifies the value of a weight differently for each spreading of the activation through the network. Such noise has a positive effect on the evolutionary increase in fitness and it makes fitness less dependent on the initial choice…