TY - GEN
T1 - Exact-bound analyzes and optimal strategies for mastermind with a lie
AU - Huang, Li Te
AU - Chen, Shan Tai
AU - Lin, Shun Shii
PY - 2006
Y1 - 2006
N2 - This paper presents novel and systematic algorithms to solve a variant of the Mastermind game, which is called "Mastermind with a Lie". Firstly, we use the k-way-branching(KWB) algorithm to get an upper bound of the number of guesses for the problem. With the help of clustering technique, the KWB algorithm is able to obtain near-optimal results effectively and efficiently. Secondly, we propose a fast backtracking(PPBFB) algorithm based on the pigeonhole principle to get the lower bounds of the number of guesses. That is a computer-aided approach, which is able to estimate the depth of the game tree and to backtrack when the depth is larger than a predefined value. Moreover, we also develop two novel methods, named "volume-renewing" and "preprocessing". They can improve the precision in the estimation of the lower bound and speed up the game tree search. As a result of applying the KWB algorithm and the PPBFB algorithm, we are able to show that the upper bound is 7 and that is also the lower bound. Thus, the problem is solved completely and the exact bound of the number of guesses for the problem is 7.
AB - This paper presents novel and systematic algorithms to solve a variant of the Mastermind game, which is called "Mastermind with a Lie". Firstly, we use the k-way-branching(KWB) algorithm to get an upper bound of the number of guesses for the problem. With the help of clustering technique, the KWB algorithm is able to obtain near-optimal results effectively and efficiently. Secondly, we propose a fast backtracking(PPBFB) algorithm based on the pigeonhole principle to get the lower bounds of the number of guesses. That is a computer-aided approach, which is able to estimate the depth of the game tree and to backtrack when the depth is larger than a predefined value. Moreover, we also develop two novel methods, named "volume-renewing" and "preprocessing". They can improve the precision in the estimation of the lower bound and speed up the game tree search. As a result of applying the KWB algorithm and the PPBFB algorithm, we are able to show that the upper bound is 7 and that is also the lower bound. Thus, the problem is solved completely and the exact bound of the number of guesses for the problem is 7.
UR - http://www.scopus.com/inward/record.url?scp=70349351662&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70349351662&partnerID=8YFLogxK
U2 - 10.1007/11922155_15
DO - 10.1007/11922155_15
M3 - Conference contribution
AN - SCOPUS:70349351662
SN - 3540488871
SN - 9783540488873
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 195
EP - 209
BT - Advances in Computer Games - 11th International Conference, ACG 2005, Revised Papers
T2 - 11th International Conference on Advances in Computer Games, ACG 2005
Y2 - 6 September 2005 through 9 September 2005
ER -