betterEvaluationFunction要求编写一个更好的评估值函数。这次使用了鬼魂的启发值、食物的启发值和恐惧胶囊的启发值来作为返回参数。 首先幽灵的启发值就是所有幽灵的距离,距离较远则有较高的启发值。食物的启发值则是获取最近的食物,距离近则启发值高。胶囊则是使用个数作为启发值,个数越多启发值越高。
*** PASS: test_cases/q3/4-ExactPredict.test ### Question q3: 3/3 ### Question q4 === *** q4) Exact inference full test: 0 inference errors. *** PASS: test_cases/q4/1-ExactFull.test *** q4) Exact inference full test: 0 inference errors. *** PASS: test_cases/q4/2-ExactF...
Project 1: Search Implementation of DFS (Depth First Search), BFS (Breadth First Search), UCS (Uniform Cost Search) and A* search with heuristics. Provisional grades === Question q1: 3/3 Question q2: 3/3 Question q3: 3/3 Question q4: 3/3 Question q5: 3/3 Question q6: 3/3 Questi...
Completed in 2019/06. PJ1_search PJ2_multiagent PJ3_reinforcement PJ4_Ghostbusters PJ5_machinelearning In this Project, Q4 requires me to implement a RNN myself, using ReLu for activation, including bias in the model. Packages No packages published...
Also, all of the commands that appear in this project also appear in commands.txt, for easy copying and pasting. In UNIX/Mac OS X, you can even run all these commands in order with bash commands.txt. Question 1 (3 points): Finding a Fixed Food Dot using Depth First Search In search...
test_cases/q4/0-eval-function-win-states-1.test *** PASS: test_cases/q4/0-eval-function-win-states-2.test *** PASS: test_cases/q4/0-expectimax1.test *** PASS: test_cases/q4/1-expectimax2.test *** PASS: test_cases/q4/2-one-ghost-3level.test *** PASS: test_cases/q4/3-one...
As in project 1, this project includes an autograder for you to grade your answers on your machine. This can be run on all questions with the command: python autograder.py Note: If your python refers to Python 2.7, you may need to invoke python3 autograder.py (and similarly for all ...
PJ1_search PJ2_multiagent PJ3_reinforcement PJ4_Ghostbusters PJ5_machinelearning In this Project, Q4 requires me to implement a RNN myself, using ReLu for activation, including bias in the model. Packages No packages published Languages
PJ1_search PJ2_multiagent PJ3_reinforcement PJ4_Ghostbusters PJ5_machinelearning In this Project, Q4 requires me to implement a RNN myself, using ReLu for activation, including bias in the model. Releases No releases published Packages
Project 1: SearchImplementation of DFS (Depth First Search), BFS (Breadth First Search), UCS (Uniform Cost Search) and A* search with heuristics.Provisional grades === Question q1: 3/3 Question q2: 3/3 Question q3: 3/3 Question q4: 3/3 Question q5: 3/3 Question q6: 3/3 Question...