We do not believe it is proper for the project to depend on work of PhD students, since a very important part of the experience of doing a PhD is learning how to identify a project that is worth pursuing and not too difficult. Moreover, students should have the right to change their research topics (within the broad framework of Xanibot) after learning more about the problems.
e.g. about mechanisms, architectures, representations, requirements, nature-nurture tradeoffs.
e.g. acquiring new ways of learning based on skills previously acquired through interacting with the environment.
Investigating the ontogenetic trajectory of physical and causal cognition in parrots,
if possible, using parrots bred in the laboratory.
In the longer term this might lead into a project investigating whether by providing tasks
and problems of particular kinds, we can 'scaffold' development of unusual kinds of competences,
compared with normally-reared birds.
Task domains could be 2-D sliding puzzles, or 3-D manipulation puzzles, or open-ended 3-D manipulation 'toys',
Effectors could be single point pushing devices, or grippers.
Problems could include learning about what can and cannot be done by different effectors in various configurations.
Current 3-D vision systems attempt to produce 'filled-in' surface models suitable for projecting
views of scenes from different directions.
What sorts of 3-D representations could be more useful for enabling a robot or animal to decide
what actions are possible, how they might be performed, and what their consequences are likely to be?
Including use of epistemic affordances i.e. affordances related to information available
as opposed to actions that are possible.
As explained inhttp://www.cs.bham.ac.uk/research/projects/cosy/papers/#tr0801
Architectural and representational requirements for seeing processes and affordances (2008)
using 2-D force controlled manipulanda to set up dynamically variable virtual visual and mechanical
environments to test exploratory search strategies in humans.
This may be extended to 3-D using the Phantom arm.
in collaboration between Wyatt and Miall.
recording human "point-force" manipulation of polyflaps within maze structures
After learning about what happens when a gear wheel is rotated on its axle,Ontology development.
e.g. by pushing its teeth tangentially, how can one predict what will happen
if two gear wheels are mounted with their teeth meshed and one is rotated?
Compare predicting behaviours of new configurations of strings and pulleys (discussed here (1971)).
What sorts of experiences can lead an animal or robot to realise that its current ontology is inadequate?
How can it generate an extension to the ontology?
How can alternative possible extensions be evaluated?
Kantian -- deterministic, structure-based
Humean/Bayesian -- statistical, correlation-based
(Discussed by Chappell and Sloman in these presentations:
especially competences requiring compositional semantics, and recombination of separately developed modules.
using the MR compatible force controlled manipulandum to record evoked activity
during exploration in a virtual mechanical environment, testing hypothesized self-reward for exploration
e.g. Case-based, or Explanation-based, learning.
E.g. as discussed in:
School of Computer Science
The University of Birmingham