Francisco Coelho / zugzwang

meetings.md 3.07 KB

Zugzwang Meetings

2023-02-28 | 15:00 | Looking for Application Examples

What applications are we looking for?

  • (Stochastic) Plan Generation
    • Yale-Shooting Problem
    • (Stochastic) Situation Calculus
    • Frame Problem
  • Given a Bayesian Network (or a Markov Networks):
    • Represent it.
    • Solve the common probability tasks: marginals, conditionals, parameter learning, inferring unobserved variables, sample generation, etc.
  • Given a solved ASP specification:
    • What is the marginal probability of the atom a?
    • What other probability queries are important to consider?
  • Given an unsolved ASP specification:
    • What is the probability (distribution?) of the probabilistic fact a?
    • What other questions are relevant? E.g. the distribution family of a fact?
  • Given a solved ASP specification and a set of samples:
    • How do the probabilities inferred from the specification match the ones from the empiric distribution?
  • Given two solved ASP specification and a set of samples:
    • Which specification best describes the empiric distribution?

What should be the task for the scholarship student? Use the Python API of clingo.

  1. Read a string and extract probability annotations; Associate those annotations with the respective atoms.
  2. Call clingo to get stable models.
  3. Support computation of the equivalence classes: Which functions and relations?
  4. Compute event probability using weighted model counting on the equivalence classes.
  5. Read a Bayesian Network from a file (BIF, DSC, NET, RDA, RDS, ...) and generate an annotated "ASP" specification.

2022 | AAAI | Inference and Learning with Model Uncertainty in Probabilistic Logic Programs

  • Is "Epistemic Uncertainty (EU)" the right framework for Zugzwang? How relevant are the epistemic questions in this paper to our work?
  • EU can be represented by Credal Sets, Subjective Logic and Beta Distributions?
  • Experiments made with BNs from (Kaplan and Ivanovska 2018) and larger networks from the BNLearn repository.
  • Are networks, Bayesian Networks in particular, a "good enough" pool of "example applications" to us, for now?

2023-01-10 | 15:00

  • Paper
  • Project
  • Latent Facts

2022-12-12

  • Is the project proposal ok? How long/detailed should it be?
  • Initial exploratory code event_lattice.py and EventLattice.ipynb done.
  • Start writing paper: Introduction, state of the art, motivation
    • Identify key problems
    • Target Conferences
    • KR;
    • ICLP;
    • ECAI
  • Next task for prototype:
    • Get stable models from potassco/s(casp)
    • other?

2022-12-05