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  2. Examples of Markov chains - Wikipedia

    en.wikipedia.org/wiki/Examples_of_Markov_chains

    A game of snakes and ladders or any other game whose moves are determined entirely by dice is a Markov chain, indeed, an absorbing Markov chain. This is in contrast to card games such as blackjack, where the cards represent a 'memory' of the past moves. To see the difference, consider the probability for a certain event in the game.

  3. Transition-rate matrix - Wikipedia

    en.wikipedia.org/wiki/Transition-rate_matrix

    In probability theory, a transition-rate matrix (also known as a Q-matrix, [1] intensity matrix, [2] or infinitesimal generator matrix [3]) is an array of numbers describing the instantaneous rate at which a continuous-time Markov chain transitions between states.

  4. Markov chain - Wikipedia

    en.wikipedia.org/wiki/Markov_chain

    Instead of defining to represent the total value of the coins on the table, we could define to represent the count of the various coin types on the table. For instance, X 6 = 1 , 0 , 5 {\displaystyle X_{6}=1,0,5} could be defined to represent the state where there is one quarter, zero dimes, and five nickels on the table after 6 one-by-one draws.

  5. Attribute (role-playing games) - Wikipedia

    en.wikipedia.org/wiki/Attribute_(role-playing_games)

    This listed the three "prime requisites" of the character classes before the "general" stats: strength for fighters, intelligence for magic-users, and wisdom for clerics. The attribute sequence in D&D was changed to Strength, Intelligence, Wisdom, Dexterity, Constitution, and Charisma, sometimes referred to as "SIWDCC". [ 9 ]

  6. Markov chain Monte Carlo - Wikipedia

    en.wikipedia.org/wiki/Markov_chain_Monte_Carlo

    A good chain will have rapid mixing: the stationary distribution is reached quickly starting from an arbitrary position. A standard empirical method to assess convergence is to run several independent simulated Markov chains and check that the ratio of inter-chain to intra-chain variances for all the parameters sampled is close to 1. [22] [23]

  7. Markov decision process - Wikipedia

    en.wikipedia.org/wiki/Markov_decision_process

    Value iteration starts at = and as a guess of the value function. It then iterates, repeatedly computing V i + 1 {\displaystyle V_{i+1}} for all states s {\displaystyle s} , until V {\displaystyle V} converges with the left-hand side equal to the right-hand side (which is the " Bellman equation " for this problem [ clarification needed ] ).

  8. Rainbow table - Wikipedia

    en.wikipedia.org/wiki/Rainbow_table

    A final postprocessing pass can sort the chains in the table and remove any "duplicate" chains that have the same final values as other chains. New chains are then generated to fill out the table. These chains are not collision-free (they may overlap briefly) but they will not merge, drastically reducing the overall number of collisions.

  9. Radar chart - Wikipedia

    en.wikipedia.org/wiki/Radar_chart

    For example, in a chart with 5 variables that range from 1 to 100, the area contained by the polygon bounded by 5 points when all measures are 90, is more than 10% larger than the same for a chart with all values of 82. Radar charts can also become hard to visually compare between different samples on the chart when their values are close as ...