martijn van otterlo xvviyijcsutwentenl dear reader comprehensive survey relational reinforcement learning available webpage survey reinforcement learning relational domains van otterlo trctit0531 70pp ctit technical report series issn 13813625 abstract reinforcement learning developed primary approach learning control strategies autonomous agents however work focused algorithmic aspect ie various ways computing value functions policies usually representational aspects limited use attributevalue propositional languages describe states actions etc recent direction general name relational reinforcement learning concerned upgrading representation reinforcement learning methods firstorder case able speak reason learn objects relations objects survey aims presenting introduction new field starting classical reinforcement learning framework describe main motivations challenges give comprehensive survey methods proposed literature aim give complete survey available literature underlying motivations implications new methods learning large relational probabilistic environments work underway provide updated version soon comments suggestions pointers new work yet appear survey greatly appreciated regards martijn van otterlo httpwwwcsutwentenlotterlo thu 07 aug 2008 051237 0200 uai relational rl survey