  The ability to make decisions and to assess potential courses of action is a
corner-stone of many AI applications, and usually this requires explicit
information about the decision-maker s preferences. IN many applications,
preference elicitation IS a serious bottleneck.The USER either does NOT have
the time, the knowledge, OR the expert support required TO specify complex
multi - attribute utility functions. IN such cases, a method that IS based ON
intuitive, yet expressive, preference statements IS required. IN this paper we
suggest the USE OF TCP - nets, an enhancement OF CP - nets, AS a tool FOR
representing, AND reasoning about qualitative preference statements.We present
AND motivate this framework, define its semantics, AND show how it can be used
TO perform constrained optimization.
