Assessment info

check learning goals on canvas.

everything in working groups (this means go through the sheets again)

• informed search (DF, BF, DFID)
• uninformed search (Hill Climbing, BF, A, A*)
• adversarial search (minimax with alpha-beta)
• logical representations
• DPLL
• uncertainty representations
• Bayesian learning
• NN/Deep learning

research procedure

• take at least 4 bots you implemented
• compare performance – play against each other, in different environments
• study results: outperforming, speed
• define interesting hypotheses and research questions, use analysis to verify/falsify them

scientific paper structure:

• title page with abstract
  • title and authors
  • abstract of 2-3 paragraphs
• introduction: intro to problem, solution, some results (2 pages)
• background info
  • describe game, challenge, IS framework, whatever else is needed (1-2 pages)
• research question
  • describe approach
  • what are:
    • possible outcomes of setup and contribution
    • e.g. whether one method works, whether it works better than others
  • also, define “working better”
• experimental setup (2 pages)
  • explain how experiments were set up
  • what you did in terms of implementation
  • compare different methods
  • define metrics
• results (2 pages)
  • describe results in overview tables
  • point reader to most significant, interesting results
• findings
• conclusions