Competition
Non-probabilistic track: results
There was a single entry in the non-probabilistic track of the competition. The entry used the Inspire system and was by Peter Schüller of Marmara University. For details of this entry see this document. A break down of the results is shown below. To see how the system performed on various types of problem, you can use the checkboxes. The table, and average accuracy will update accordingly.
| Include Problems without: | |
| Include Problems with: | |
| Tasks with small language biases, are tasks where the list of relevant predicates given to the learner contain only the predicates needed to explain the examples. Medium sized language biases contain an extra, irrelevant predicate, and large language biases contain at least two extra irrelevant predicates. Note that in tasks that required predicate invention, the invented predicates were not given to the learner. | |
Note that in the table below, the list of properties is exhaustive. So, for example, if a problem does not have recursion in its list of properties, then it is possible to explain the examples without recursion. You can see details of the problem, together with the test traces and the final attempt made by the learner to classify these traces by clicking on the "problem details and system output" links.
| Problem Name | Properties | Accuracy | Details |
|---|---|---|---|
| Hurdler | non probabilistic; recursion; small language bias | 1.0 | problem details and system output |
| Hurdler | non probabilistic; recursion; medium language bias | 1.0 | problem details and system output |
| Hurdler | non probabilistic; recursion; large language bias | 1.0 | problem details and system output |
| Revisit | non probabilistic; predicate invention; recursion; small language bias | 0.0 | problem details and system output |
| Revisit | non probabilistic; predicate invention; recursion; medium language bias | 0.0 | problem details and system output |
| Revisit | non probabilistic; predicate invention; recursion; large language bias | 0.75 | problem details and system output |
| Fast agent | non probabilistic; predicate invention; recursion; small language bias | 0.0 | problem details and system output |
| Fast agent | non probabilistic; predicate invention; recursion; medium language bias | 0.0 | problem details and system output |
| Fast agent | non probabilistic; predicate invention; recursion; large language bias | 0.0 | problem details and system output |
| one way | non probabilistic; small language bias | 1.0 | problem details and system output |
| one way | non probabilistic; medium language bias | 1.0 | problem details and system output |
| one way | non probabilistic; large language bias | 1.0 | problem details and system output |
| security camera | non probabilistic; non observational predicate learning; non monotonic; small language bias | 0.0 | problem details and system output |
| security camera | non probabilistic; non observational predicate learning; non monotonic; medium language bias | 0.0 | problem details and system output |
| security camera | non probabilistic; non observational predicate learning; non monotonic; large language bias | 0.0 | problem details and system output |
| mirror | non probabilistic; small language bias | 1.0 | problem details and system output |
| mirror | non probabilistic; medium language bias | 1.0 | problem details and system output |
| mirror | non probabilistic; large language bias | 1.0 | problem details and system output |
| trespass | non probabilistic; predicate invention; non monotonic; small language bias | 1.0 | problem details and system output |
| trespass | non probabilistic; predicate invention; non monotonic; medium language bias | 1.0 | problem details and system output |
| trespass | non probabilistic; predicate invention; non monotonic; large language bias | 1.0 | problem details and system output |
| no second chances | non probabilistic; predicate invention; non monotonic; recursion; small language bias | 0.0 | problem details and system output |
| no second chances | non probabilistic; predicate invention; non monotonic; recursion; medium language bias | 0.0 | problem details and system output |
| no second chances | non probabilistic; predicate invention; non monotonic; recursion; large language bias | 0.0 | problem details and system output |
| patrol | non probabilistic; non monotonic; small language bias | 0.0 | problem details and system output |
| patrol | non probabilistic; non monotonic; medium language bias | 0.0 | problem details and system output |
| patrol | non probabilistic; non monotonic; large language bias | 0.0 | problem details and system output |
| granted access | non probabilistic; recursion; small language bias | 0.0 | problem details and system output |
| granted access | non probabilistic; recursion; medium language bias | 0.0 | problem details and system output |
| granted access | non probabilistic; recursion; large language bias | 0.0 | problem details and system output |
| diagonal | non probabilistic; non observational predicate learning; small language bias | 1.0 | problem details and system output |
| diagonal | non probabilistic; non observational predicate learning; medium language bias | 1.0 | problem details and system output |
| diagonal | non probabilistic; non observational predicate learning; large language bias | 1.0 | problem details and system output |
| injured_agent | non probabilistic; non monotonic; small language bias | 0.6666666666666666 | problem details and system output |
| injured_agent | non probabilistic; non monotonic; medium language bias | 1.0 | problem details and system output |
| injured_agent | non probabilistic; non monotonic; large language bias | 1.0 | problem details and system output |
| barrier | non probabilistic; non monotonic; recursion; small language bias | 0.0 | problem details and system output |
| barrier | non probabilistic; non monotonic; recursion; medium language bias | 0.0 | problem details and system output |
| barrier | non probabilistic; non monotonic; recursion; large language bias | 0.0 | problem details and system output |
| recursive patrol | non probabilistic; predicate invention; non monotonic; recursion; small language bias | 0.0 | problem details and system output |
| recursive patrol | non probabilistic; predicate invention; non monotonic; recursion; medium language bias | 0.0 | problem details and system output |
| recursive patrol | non probabilistic; predicate invention; non monotonic; recursion; large language bias | 0.0 | problem details and system output |
| nonOPL recursive patrol | non probabilistic; non observational predicate learning; non monotonic; recursion; small language bias | 1.0 | problem details and system output |
| nonOPL recursive patrol | non probabilistic; non observational predicate learning; non monotonic; recursion; medium language bias | 0.1875 | problem details and system output |
| nonOPL recursive patrol | non probabilistic; non observational predicate learning; non monotonic; recursion; large language bias | 0.9375 | problem details and system output |