Editing Walking (section)

=== Control based models ===
Control-based models start with a simulation based on some description of the animal's anatomy and optimize control parameters to generate some behavior. These may be based on a musculoskeletal model,<ref>{{Cite journal |last1=Geijtenbeek |first1=Thomas |last2=van de Panne |first2=Michiel |last3=van der Stappen |first3=A. Frank |date=November 2013 |title=Flexible muscle-based locomotion for bipedal creatures |url=http://dx.doi.org/10.1145/2508363.2508399 |journal=ACM Transactions on Graphics |volume=32 |issue=6 |pages=1–11 |doi=10.1145/2508363.2508399 |s2cid=9183862 |issn=0730-0301}}</ref> skeletal model,<ref>{{cite arXiv | eprint=1707.02286 | last1=Heess | first1=Nicolas | last2=TB | first2=Dhruva | last3=Sriram | first3=Srinivasan | last4=Lemmon | first4=Jay | last5=Merel | first5=Josh | last6=Wayne | first6=Greg | last7=Tassa | first7=Yuval | last8=Erez | first8=Tom | last9=Wang | first9=Ziyu | last10=Ali Eslami | first10=S. M. | last11=Riedmiller | first11=Martin | last12=Silver | first12=David | title=Emergence of Locomotion Behaviours in Rich Environments | year=2017 | class=cs.AI }}</ref><ref>{{Cite journal |last1=Peng |first1=Xue Bin |last2=Abbeel |first2=Pieter |last3=Levine |first3=Sergey |last4=van de Panne |first4=Michiel |date=2018-08-31 |title=DeepMimic |url=http://dx.doi.org/10.1145/3197517.3201311 |journal=ACM Transactions on Graphics |volume=37 |issue=4 |pages=1–14 |doi=10.1145/3197517.3201311 |arxiv=1804.02717 |s2cid=215808400 |issn=0730-0301}}</ref> or even simply a ball and stick model.<ref>{{Cite journal |last1=Szczecinski |first1=Nicholas S. |last2=Bockemühl |first2=Till |last3=Chockley |first3=Alexander S. |last4=Büschges |first4=Ansgar |date=2018-11-16 |title=Static stability predicts the continuum of interleg coordination patterns in Drosophila |journal=Journal of Experimental Biology |volume=221 |issue=22 |pages=jeb189142 |doi=10.1242/jeb.189142 |pmid=30274987 |s2cid=52903595 |issn=0022-0949|doi-access=free }}</ref> As these models generate locomotion by optimizing some metric, they can be used to explore the space of optimal locomotion behaviors under some assumptions. However, they typically do not generate plausible hypotheses on the neural coding underlying the behaviors and are typically sensitive to modeling assumptions.