Research - Requirements

Adaptron must be able to learn and think using any combination of the following robot features.

The ultimate objective is to handle all the higher complexity settings.

Features Low Complexity High Complexity
Number of senses One Multiple
Sensors per sense One Multiple
Multiple Sensors Independent sensors Dependent sensor array - one dimension
Sensor array Linear Circular
Number of sensor arrays One Dimension Two Dimensions (not currently a requirement)
Type of readings / inputs Symbolic (Nominal) Magnitude (Ratio scale )
Number of action device types One Multiple
Number of action devices per type One Multiple
Simultaneous actions One at a time per device Multiple in parallel

Value Systems

(Motivation –> Behaviour)

Familiar / Unfamiliar

(Intrinsic –> Exploration)

Emotional feelings

(Extrinsic –> Survival)

Thinking ahead One stimulus Multiple steps
Time flow Event driven Clock driven

Other constraints that have been imposed on the design of Adaptron are:

  • It is to be programmed using a deterministic algorithm, no probabilities
  • It is to be as simple as possible; Occam’s Razor applies
  • It is to start with no experience; it must learn everything; 100% grounded, embodied and enactive
  • It is to operate within a robot body which is separate from the environment
  • The robot body shall house the sensors and action devices
  • It is to start with two built in value systems, one for exploration and the other for survival
  • It shall use reinforcement learning driven by the value systems for learning actions
  • It will use unsupervised learning for perception ( not supervised learning )