TY - GEN
T1 - Detecting Unknots via Equational Reasoning, I: Exploration
AU - Fish, Andrew
AU - Lisitsa, Alexei
PY - 2014/1/1
Y1 - 2014/1/1
N2 - We explore the application of automated reasoning techniques to unknot detection, a classical problem of computational topology. We adopt a two-pronged experimental approach, using a theorem prover to try to establish a positive result (i.e. that a knot is the unknot), whilst simultaneously using a model finder to try to establish a negative result (i.e. that the knot is not the unknot). The theorem proving approach utilises equational reasoning, whilst the model finder searches for a minimal size counter-model. We present and compare experimental data using the involutary quandle of the knot, as well as comparing with alternative approaches, highlighting instances of interest. Furthermore, we present theoretical connections of the minimal countermodels obtained with existing knot invariants, for all prime knots of up to 10 crossings: this may be useful for developing advanced search strategies.
AB - We explore the application of automated reasoning techniques to unknot detection, a classical problem of computational topology. We adopt a two-pronged experimental approach, using a theorem prover to try to establish a positive result (i.e. that a knot is the unknot), whilst simultaneously using a model finder to try to establish a negative result (i.e. that the knot is not the unknot). The theorem proving approach utilises equational reasoning, whilst the model finder searches for a minimal size counter-model. We present and compare experimental data using the involutary quandle of the knot, as well as comparing with alternative approaches, highlighting instances of interest. Furthermore, we present theoretical connections of the minimal countermodels obtained with existing knot invariants, for all prime knots of up to 10 crossings: this may be useful for developing advanced search strategies.
U2 - 10.1007%2F978-3-319-08434-3_7
DO - 10.1007%2F978-3-319-08434-3_7
M3 - Conference contribution with ISSN or ISBN
SN - 9783319084336
VL - 8543
T3 - Lecture Notes in Computer Science
SP - 76
EP - 91
BT - Intelligent Computer Mathematics International Conference, CICM 2014
PB - Springer International Publishing
CY - Portugal
T2 - Intelligent Computer Mathematics International Conference, CICM 2014
Y2 - 1 January 2014
ER -