lectures.alex.balgavy.eu

Lecture notes from university.
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     11 <div id="Assessment info"><h1 id="Assessment info">Assessment info</h1></div>
     12 <p>
     13 check learning goals on canvas.
     14 </p>
     15 
     16 <p>
     17 everything in working groups (this means go through the sheets again)
     18 </p>
     19 <ul>
     20 <li>
     21 informed search (DF, BF, DFID)
     22 
     23 <li>
     24 uninformed search (Hill Climbing, BF, A, A*)
     25 
     26 <li>
     27 adversarial search (minimax with alpha-beta)
     28 
     29 <li>
     30 logical representations
     31 
     32 <li>
     33 DPLL
     34 
     35 <li>
     36 uncertainty representations
     37 
     38 <li>
     39 Bayesian learning
     40 
     41 <li>
     42 NN/Deep learning
     43 
     44 </ul>
     45 
     46 <p>
     47 research procedure
     48 </p>
     49 <ul>
     50 <li>
     51 take at least 4 bots you implemented
     52 
     53 <li>
     54 compare performance -- play against each other, in different environments
     55 
     56 <li>
     57 study results: outperforming, speed
     58 
     59 <li>
     60 define interesting hypotheses and research questions, use analysis to verify/falsify them
     61 
     62 </ul>
     63 
     64 <p>
     65 scientific paper structure:
     66 </p>
     67 <ul>
     68 <li>
     69 title page with abstract
     70 
     71 <ul>
     72 <li>
     73 title and authors
     74 
     75 <li>
     76 abstract of 2-3 paragraphs
     77 
     78 </ul>
     79 <li>
     80 introduction: intro to problem, solution, some results (2 pages)
     81 
     82 <li>
     83 background info
     84 
     85 <ul>
     86 <li>
     87 describe game, challenge, IS framework, whatever else is needed (1-2 pages)
     88 
     89 </ul>
     90 <li>
     91 research question
     92 
     93 <ul>
     94 <li>
     95 describe approach
     96 
     97 <li>
     98 what are:
     99 
    100 <ul>
    101 <li>
    102 possible outcomes of setup and contribution
    103 
    104 <li>
    105 e.g. whether one method works, whether it works better than others
    106 
    107 </ul>
    108 <li>
    109 also, define "working better"
    110 
    111 </ul>
    112 <li>
    113 experimental setup (2 pages)
    114 
    115 <ul>
    116 <li>
    117 explain how experiments were set up
    118 
    119 <li>
    120 what you did in terms of implementation
    121 
    122 <li>
    123 compare different methods
    124 
    125 <li>
    126 define metrics
    127 
    128 </ul>
    129 <li>
    130 results (2 pages)
    131 
    132 <ul>
    133 <li>
    134 describe results in overview tables
    135 
    136 <li>
    137 point reader to most significant, interesting results
    138 
    139 </ul>
    140 <li>
    141 findings
    142 
    143 <li>
    144 conclusions
    145 
    146 </ul>
    147 
    148 </body>
    149 </html>