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.+In+the+realm+of+theory%252C+we+prove+that+the+new+constraints+provide+lower+bounds+on+the+cost+of+plans+that+comply+with+observations.+We+also+provide+an+extensive+empirical+evaluation+to+assess+how+the+new+constraints+improve+the+quality+of+the+solution%252C+and+we+found+that+they+are+especially+informed+in+deciding+which+goals+are+unlikely+to+be+part+of+the+solution.+Our+novel+recognition+approaches+have+two+pivotal+advantages%3a+first%252C+they+employ+new+IP%252FLP+constraints+for+efficiently+recognizing+goals%253B+second%252C+we+show+how+the+new+IP%252FLP+constraints+can+improve+the+recognition+of+goals+under+both+partial+and+noisy+observability.&cdnurl=https%3a%2f%2fth.bing.com%2fth%2fid%2fR.66c1141e8e4ac61f8ef56d8f67cffae7%3frik%3d%252f2EyCskzzbUtSw%26pid%3dImgRaw%26r%3d0&exph=630&expw=1200&q=Difference+Between+Linear+Programming+and+Goal+Programming&FORM=IRPRST&ck=2A70BB3FB6C3ABA8CA159B1B5F9B8CE0&selectedIndex=28&itb=0)
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