TY - JOUR
T1 - Analyzing behavior implied by EWA learning
T2 - An emphasis on distinguishing reinforcement from belief learning
AU - van der Horst, W.
AU - van Assen, M.A.L.M.
AU - Snijders, C.C.P.
PY - 2010/4
Y1 - 2010/4
N2 - An important issue in the field of learning is to what extent one can distinguish between behavior resulting from either belief or reinforcement learning. Previous research suggests that it is difficult or even impossible to distinguish belief from reinforcement learning: belief and reinforcement models often fit the empirical data equally well. However, previous research has been confined to specific games in specific settings. In the present study we derive predictions for behavior in games using the EWA learning model (e.g., Camerer & Ho, 1999), a model that includes belief learning and a specific type of reinforcement learning as special cases. We conclude that belief and reinforcement learning can be distinguished, even in 2×2 games. Maximum differentiation in behavior resulting from either belief or reinforcement learning is obtained in games with pure Nash equilibria with negative payoffs and at least one other strategy combination with only positive payoffs. Our results help researchers to identify games in which belief and reinforcement learning can be discerned easily.
AB - An important issue in the field of learning is to what extent one can distinguish between behavior resulting from either belief or reinforcement learning. Previous research suggests that it is difficult or even impossible to distinguish belief from reinforcement learning: belief and reinforcement models often fit the empirical data equally well. However, previous research has been confined to specific games in specific settings. In the present study we derive predictions for behavior in games using the EWA learning model (e.g., Camerer & Ho, 1999), a model that includes belief learning and a specific type of reinforcement learning as special cases. We conclude that belief and reinforcement learning can be distinguished, even in 2×2 games. Maximum differentiation in behavior resulting from either belief or reinforcement learning is obtained in games with pure Nash equilibria with negative payoffs and at least one other strategy combination with only positive payoffs. Our results help researchers to identify games in which belief and reinforcement learning can be discerned easily.
KW - Belief learning
KW - EWA learning
KW - Reinforcement learning
KW - Stable strategy combinations
UR - http://www.scopus.com/inward/record.url?scp=77949873664&partnerID=8YFLogxK
U2 - 10.1016/j.jmp.2009.11.002
DO - 10.1016/j.jmp.2009.11.002
M3 - Article
AN - SCOPUS:77949873664
SN - 0022-2496
VL - 54
SP - 222
EP - 229
JO - Journal of Mathematical Psychology
JF - Journal of Mathematical Psychology
IS - 2
ER -