0001-Add-a-BayesNetwork-proto-description.patch
| proto/sandbox/rst/graph/BayesNetwork.proto | ||
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package rst.graph; |
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import "rst/graph/BayesVariable.proto"; |
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option java_outer_classname = "BayesNetworkType"; |
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/** |
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* The BayesNetwork message holds the description of a bayesian network |
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* following the XMLBIF Format: |
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* |
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* <!DOCTYPE BIF [ |
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* <!ELEMENT BIF ( NETWORK )*> |
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* <!ATTLIST BIF VERSION CDATA #REQUIRED> |
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* <!ELEMENT NETWORK ( NAME, ( PROPERTY | VARIABLE | DEFINITION )* )> |
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* <!ELEMENT NAME (#PCDATA)> |
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* <!ELEMENT VARIABLE ( NAME, ( OUTCOME | PROPERTY )* ) > |
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* <!ATTLIST VARIABLE TYPE (nature|decision|utility) "nature"> |
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* <!ELEMENT OUTCOME (#PCDATA)> |
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* <!ELEMENT DEFINITION ( FOR | GIVEN | TABLE | PROPERTY )* > |
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* <!ELEMENT FOR (#PCDATA)> |
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* <!ELEMENT GIVEN (#PCDATA)> |
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* <!ELEMENT TABLE (#PCDATA)> |
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* <!ELEMENT PROPERTY (#PCDATA)> |
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* ]> |
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* |
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* See: http://www.cs.cmu.edu/afs/cs/user/fgcozman/www/Research/InterchangeFormat/ |
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* |
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* @author Viktor Richter <vrichter@techfak.uni-bielefeld.de> |
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*/ |
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message BayesNetwork {
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/** |
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* The name of this BayesNetwork |
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*/ |
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optional string name = 1; |
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/** |
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* Arbitrary properties associated with the network. |
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*/ |
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repeated string property = 2; |
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/** |
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* List of the BayesVariables describing the nodes of the network in |
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* combination with theyr connectivity and conditional probability |
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* distribution. |
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*/ |
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repeated BayesVariable variable = 3; |
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} |
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| proto/sandbox/rst/graph/BayesVariable.proto | ||
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package rst.graph; |
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option java_outer_classname = "BayesVariableType"; |
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/** |
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* BayesVariable used in a BayesNetwork. |
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* Describes a variable with its possible outcomes. |
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* |
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* @author Viktor Richter <vrichter@techfak.uni-bielefeld.de> |
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*/ |
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message BayesVariable {
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/** |
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* Enum describing the type of a BayesVariable. |
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*/ |
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enum Type {
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/** |
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* A Simple Variable in the BayesNetwork representing a world state. |
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*/ |
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NATURE = 1; |
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/** |
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* Represents an action to choose from. |
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*/ |
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DECISION = 2; |
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/** |
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* Represents the quality or benefit of a decision. |
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*/ |
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UTILITY = 3; |
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} |
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/** |
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* The name of the Variable. This has to be unique in a bayes Network. |
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*/ |
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optional string name = 1; |
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/** |
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* The Type of the Variable. |
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*/ |
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optional Type type = 2; |
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/** |
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* The possible outcomes (states) of the variables. |
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*/ |
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repeated string outcomes = 3; |
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/** |
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* Arbitrary properties associated with the variable. |
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*/ |
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repeated string property = 4; |
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/** |
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* The variables on which state this BayesVariable depends. |
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*/ |
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repeated string parents = 5; |
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/** |
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* The conditional probability table describing the probability |
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* of each outcome of this variable for each combination of the |
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* parents states. |
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* |
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* The cpt holds the probability values for the variable outcomes |
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* in the order \f$ v_1, \dots, v_n, v_0 \f$ with the value |
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* permutation from right to left. |
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* |
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* \verbatim |
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* An example with three binary variables would look the following way: |
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* |
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* | parent1 | parent2 | variable | position in table | |
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* ---------------------------------------------------- |
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* | 0 | 0 | 0 | 0 | |
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* | 0 | 0 | 1 | 1 | |
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* | 0 | 1 | 0 | 2 | |
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* | 0 | 1 | 1 | 3 | |
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* | 1 | 0 | 0 | 4 | |
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* | 1 | 0 | 1 | 5 | |
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* | 1 | 1 | 0 | 6 | |
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* | 1 | 1 | 1 | 7 | |
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* \endverbatim |
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*/ |
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repeated double probabilities = 6; |
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} |
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- |
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