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.+NeuCF+is+a+recently+developed+bio-inspired+model+for+target+tracking+based+on+Dynamic+Neural+Fields+(DNFs)+and+Stochastic+Optimal+Control+(SOC)+theory.+It+has+been+trained+for+reaching+actions+on+a+planar+surface+toward+localized+visual+beacons%252C+and+it+can+re-target+or+generate+stop+signals+on+the+fly+based+on+changes+in+the+environment+(e.g.%252C+a+new+target+has+emerged%252C+or+an+existing+one+has+been+removed).+We+evaluated+our+system+over+various+target-reaching+scenarios.+In+all+experiments%252C+NeuCF+had+high+end-effector+positional+accuracy%252C+generated+smooth+trajectories%252C+and+provided+reduced+path+lengths+compared+with+a+baseline+cubic+polynomial+trajectory+generator.+In+all%252C+the+developed+system+offers+a+robust+and+dynamic-aware+robotic+manipulation+approach+that+affords+real-time+decision-making.&cdnurl=https%3a%2f%2fth.bing.com%2fth%2fid%2fR.53081eea784fb003b053aa3e21caa8d6%3frik%3dDnTZYWIVbo4Rug%26pid%3dImgRaw%26r%3d0&exph=630&expw=1200&q=Agent-Based+Model&FORM=IRPRST&ck=16B10825134524C4881F42CEBC9AD5D7&selectedIndex=14&itb=0)
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