Planning and organization of one's actions are crucial for successfully performing everyday activities such as setting the table. While existing research has addressed planning for well-defined tasks and control of already established sequences, little is known about how such sequences are planned in ill-defined tasks such as everyday activities. Initial attempts suggest that planning may be opportunistic, based on a number of environmental factors to minimize cognitive and physical effort. We address two questions arising from the existing work: First, to what extent is variation in human everyday activity behavior captured by the proposed opportunistic consideration of environmental factors? We address this questions by employing machine learning baselines to gauge the proposed models explanatory scope. Second, to what extent are existing models of sequence control consistent with opportunistic action organization? We address this by investigating and discussing the implications opportunistic planning has for the mechanisms currently assumed for sequence control.

The action order of most everyday activities is only weaklyconstrained: When setting the table, for example, the orderin which the items are placed on the table does not matter ifall required items are on the table eventually. Little is knownabout how humans deal with weakly constrained sequences.Consistent with research on local optimality of human behav-ior and the “law of less work”, we propose that the order ofweakly constrained sequences is not chosen arbitrarily but dueto preferences, with the overall goal to minimize cognitive andphysical effort. We implement and validate a stepwise-optimalmodel for table setting, revealing ordering preferences basedon distance, functional relations between items, and reachabil-ity. The model’s success has implications concerning actionorganization in weakly constrained sequences as well as con-trol of action sequences and provides further evidence on thequestion of global vs. local optimality of human cognition.