73 lines
2.3 KiB
Plaintext
73 lines
2.3 KiB
Plaintext
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%%%% Double coin tossing --- dcoin.psm
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%%%%
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%%%% Copyright (C) 2004,2006,2008
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%%%% Sato Laboratory, Dept. of Computer Science,
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%%%% Tokyo Institute of Technology
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%% A sequential mixture of two Bernoulli trials processes.
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%% We have two coins, coin(1) and coin(2).
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%% Start with coin(1), we keep flipping a coin and observe the outcome.
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%% We change coins according to the rule in the process.
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%% If the outcome is "head", the next coin to flip is coin(2).
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%% If the outcome is "tail", the next coin to flip is coin(1).
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%% The learning task is to estimate parameters for coin(1) and coin(2),
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%% observing a sequence of outcomes.
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%% As there is no hidden variable in this model, EM learning is just
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%% ML estimation from complete data.
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%%-------------------------------------
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%% Quick start : sample session
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%%
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%% (1) load this program
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%% ?- prism(dcoin).
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%%
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%% (2) sampling and probability computations
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%% ?- sample(dcoin(10,X)),prob(dcoin(10,X)).
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%% ?- sample(dcoin(10,X)),probf(dcoin(10,X)).
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%%
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%% (3) EM learning
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%% ?- go.
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go:- dcoin_learn(500).
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%%------------------------------------
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%% Declarations:
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values(coin(1),[head,tail],[0.5,0.5]).
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% Declare msw(coin(1),V) s.t. V = head or
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% V = tail, where P(msw(coin(1),head)) = 0.5
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% and P(msw(coin(1),tail)) = 0.5.
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values(coin(2),[head,tail],[0.7,0.3]).
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% Declare msw(coin(2),V) s.t. V = head or
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% V = tail, where P(msw(coin(2),head)) = 0.7
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% and P(msw(coin(2),tail)) = 0.3.
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%%------------------------------------
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%% Modeling part:
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dcoin(N,Rs) :- % Rs is a list with length N of outcomes
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dcoin(N,coin(1),Rs). % from two Bernoulli trials processes.
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dcoin(N,Coin,[R|Rs]) :-
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N > 0,
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msw(Coin,R),
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( R == head, NextCoin = coin(2)
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; R == tail, NextCoin = coin(1) ),
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N1 is N-1,
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dcoin(N1,NextCoin,Rs).
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dcoin(0,_,[]).
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%%------------------------------------
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%% Utility part:
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dcoin_learn(N) :-
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set_params, % Set parameters.
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sample(dcoin(N,Rs)), % Get a sample Rs of size N.
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Goals = [dcoin(N,Rs)], % Estimate the parameters from Rs.
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learn(Goals).
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set_params :-
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set_sw(coin(1),[0.5,0.5]),
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set_sw(coin(2),[0.7,0.3]).
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