The invention relates to the field of control and computing technologies. A method is provided for building an inference path in a knowledge base comprising a representation of a model of a subject domain in the form of objects and links arranged in an oriented bipartite graph. The objects contain parameters, and the links contain rules; each rule has an input variable and an output variable, and each parameter linked with a rule is either an input variable or an output variable of the rule. A collection of known parameters is generated, and one or more required parameters are specified. The method comprises performing processing with respect to each known parameter which has not undergone the processing before, in order to find the required parameters. The processing comprises: determining launchable rules in which the known parameter is an input variable, for which all remaining input variables are known, and which have not been launched before; launching the determined launchable rules and adding output variables of the launched rules to the collection of known parameters; if all the required parameters are found, the processing is terminated. A sequence of launched rules is formed in the order in which they were launched; the sequence represents the inference path.
Please help me write a proper abstract based on the patent claims. CLAIM: 1-36. (canceled) 37. A computer-implemented method of automatedly building an inference path in a knowledge base comprising a representation of a model of a domain as objects and links arranged in an oriented bipartite graph, wherein the objects include parameters, and the links include rules, and wherein each rule has at least one input variable and at least one output variable, and each parameter associated with a rule is either an input variable or an output variable of the rule; said method comprising: generating a collection of known parameters and specifying one or more required parameters; performing processing with respect to each known parameter which has not undergone said processing before, in order to find the required parameters, said processing comprising: determining launchable rules wherein: the known parameter is an input variable in the launchable rules, all remaining input variables are known for the launchable rules, and the launchable rules have not been launched before; simultaneously launching multiple said determined launchable rules and adding output variables of the launched rules to the collection of known parameters, and carrying out analysis regarding achievement of a goal, wherein simulation of launching a rule is performed by assigning values “known” to variables outputted in said rule; and if all the required parameters are found, terminating the processing and identifying a problem as solved; otherwise, performing subsequent search for the inference path; and building a sequence of the launched rules in an order in which they were launched, the built sequence of rules representing the inference path. 38. The method according to claim 37, wherein the collection of known parameters is a queue or stack, and wherein known parameters are successively retrieved from the queue or stack, respectively, to perform said processing, the method further comprising, if launchable rules have not been determined for the known parameter, retrieving a next known parameter from the queue or stack, and performing said processing with respect to the next known parameter. 39. The method according to claim 37, further comprising: outputting the found required parameters and the built inference path onto a display device; and outputting an error message and/or unfound required parameters if at least part of the required parameters has not been found as a result of said processing. 40. The method according to claim 37, further comprising entering the known parameters via a user interface. 41. The method according to claim 37, wherein for each parameter, information about all rules for which the parameter is an input or output variable is stored as at least one list; for each rule, information about all input and output variables of the rule, including information about a number of input and output variables of said rule, is stored as at least one list. 42. The method according to claim 41, wherein for each parameter found in said processing, information is further stored about a launched rule, where the parameter is an output variable, by which said parameter was found; for each launchable rule, information is further stored about a parameter among parameters, which are an input variable of said rule, that led to determination in said processing that said rule is launchable. 43. The method according to claim 41, wherein, for each rule, an indicator is further stored, the indicator indicating whether the rule was launched or not, and further comprising: after launching the rule, modifying the indicator to indicate that the rule was launched. 44. The method according to claim 37, wherein the objects further comprise classes, wherein each class may include other classes and/or parameters, and each parameter relates to only one class; the links further comprise relations, each relation describing a relationship between abstract variables, wherein each rule includes a reference to a relation. 45. The method according to claim 44, wherein said representation of the model of the domain further comprises one or more restrictions, wherein input variables of each restriction are values of parameters, each restriction comprising a reference to a relation that expresses a condition to be met by the input variables, and an output variable of each restriction is a Boolean variable. 46. The method according to claim 45, further comprising: launching at least one restriction by specifying respective known parameters as input variables of the restriction; and outputting an error message and stopping execution of the method if a condition expressed by the restriction is not satisfied by the respective known parameters. 47. The method according to claim 37, further comprising: generating a list of required parameters from said required parameters; while the list of required parameters is not empty, retrieving a required parameter from the list of required parameters and identifying a rule by which the selected required parameter was directly determined; if the identified rule has not been previously added to a global sequence of rules being generated, generating a local sequence of rules involved in determining the selected required parameter, beginning with adding the identified rule to the local sequence of rules, wherein said generating the local sequence of rules comprises, for each rule beginning from said identified rule: identifying an initiator parameter which is an input variable of the rule and which initiated launching the rule in said processing; if the rule has one or more other input variables, then adding for each of said one or more other input variables a parameter, which is said input variable, to the beginning of the list of required parameters, and determining a place for insertion of the local sequence of rules, which it to be generated for the added parameter, into the global sequence of rules, the insertion place indicating a rule before which the local sequence of rules to be generated for the added parameter should be inserted into the global sequence of rules; while said generating the local sequence of rules is not completed: selecting, from the launched rules, a rule whose output variable is said initiator parameter, and verifying whether the selected rule is present in the global sequence of rules and whether the selected rule is an insertion place; if the selected rule is present in the global sequence of rules or the selected rule is the insertion place, terminating said generating the local sequence of rules; if the selected rule is not present in the global sequence of rules and is not the insertion place, adding the selected rule to the end of the local sequence of rules being generated and verifying whether the rule is a rule whose input variables were only known parameters; and if the input variables of the selected rule were only known parameters, terminating said generating the local sequence of rules; and if an insertion place is determined for the required parameter, inserting the generated local sequence of rules into the insertion place in the global sequence of rules, otherwise adding the local sequence of rules to the end of the global sequence of rules; wherein the generated global sequence of rules represents an optimized inference path. 48. The method according to claim 47, wherein the adding the rule to the local sequence of rules further comprises: entering output variables of said rule to a list of found parameters being formed if the output variables are not present in the list of found parameters, and removing, from the list of required parameters, the required parameters which are present in the list of found parameters. 49. The method according to claim 47, wherein each of the local sequence of rules and the global sequence of rules is a list, and the list of required parameters is a linked list. 50. A computer device configured for automatedly building an inference path in a knowledge base comprising a representation of a model of a domain as objects and links arranged in an oriented bipartite graph, wherein the objects include parameters, and the links include rules, and wherein each rule has at least one input variable and at least one output variable, and each parameter associated with a rule is either an input variable or an output variable of the rule; said computer device comprising: one or more processors; and one or more data storage units having computer-executable instructions stored therein, the computer-executable instructions, when executed by the one or more processors, causing the one or more processors to: generate a collection of known parameters and specify one or more required parameters; perform processing with respect to each known parameter which has not undergone said processing before, in order to find the required parameters, said processing comprising: determining launchable rules wherein: the known parameter is an input variable in the launchable rules, all remaining input variables are known for the launchable rules, and the launchable rules have not been launched before; simultaneously launching multiple said determined launchable rules and adding output variables of the launched rules to the collection of known parameters, and carrying out analysis regarding achievement of a goal, wherein simulation of launching a rule is performed by assigning values “known” to variables outputted in said rule; and if all the required parameters are found, terminating the processing and identifying a problem as solved; otherwise, performing subsequent search for the inference path; build a sequence of the launched rules in an order in which they were launched, the built sequence of rules representing the inference path; and filter the built sequence of rules so that said sequence contains only those rules the launching of which was directly involved in finding the required parameters. 51. The device according to claim 50, wherein said filtering comprises: generating a list of required parameters from said required parameters; while the list of required parameters is not empty, retrieving a required parameter from the list of required parameters and identifying a rule by which the selected required parameter was directly determined; if the identified rule has not been previously added to a global sequence of rules being generated, generating a local sequence of rules involved in determining the selected required parameter, beginning with adding the identified rule to the local sequence of rules, wherein said generating the local sequence of rules comprises, for each rule beginning from said identified rule: identifying an initiator parameter which is an input variable of the rule and which initiated launching the rule in said processing; if the rule has one or more other input variables, then adding for each of said one or more other input variables a parameter, which is said input variable, to the beginning of the list of required parameters, and determining a place for insertion of the local sequence of rules, which it to be generated for the added parameter, into the global sequence of rules, the insertion place indicating a rule before which the local sequence of rules to be generated for the added parameter should be inserted into the global sequence of rules; while said generating the local sequence of rules is not completed: selecting, from the launched rules, a rule whose output variable is said initiator parameter, and verifying whether the selected rule is present in the global sequence of rules and whether the selected rule is an insertion place; if the selected rule is present in the global sequence of rules or the selected rule is the insertion place, terminating said generating the local sequence of rules; if the selected rule is not present in the global sequence of rules and is not the insertion place, adding the selected rule to the end of the local sequence of rules being generated and verifying whether the rule is a rule whose input variables were only known parameters, and if the input variables of the selected rule were only known parameters, terminating said generating the local sequence of rules; and if an insertion place is determined for the required parameter, inserting the generated local sequence of rules into the insertion place in the global sequence of rules, otherwise adding the local sequence of rules to the end of the global sequence of rules; wherein the generated global sequence of rules represents an optimized inference path. 52. The device according to claim 51, wherein the adding the rule to the local sequence of rules further comprises: entering output variables of said rule to a list of found parameters being formed if the output variables are not present in the list of found parameters, and removing, from the list of required parameters, the required parameters which are present in the list of found parameters. 53. The device according to claim 51, wherein each of the local sequence of rules and the global sequence of rules is a list, and the list of required parameters is a linked list. 54. The device according to claim 50, wherein for each parameter, information about all rules for which the parameter is an input or output variable is stored as at least one list; for each rule, information about all input and output variables of the rule, including information about a number of input and output variables of said rule, is stored as at least one list. 55. The device according to claim 54, wherein for each parameter found in said processing, information is further stored about a launched rule, where the parameter is an output variable, by which said parameter was found; for each launchable rule, information is further stored about a parameter among parameters, which are an input variable of said rule, that led to determination in said processing that said rule is launchable; for each rule, an indicator is further stored, the indicator indicating whether the rule was launched or not, and further comprising: after launching the rule, modifying the indicator to indicate that the rule was launched. 56. A computer-readable storage medium having computer-executable instructions stored therein, the computer-executable instructions, when executed, causing a computer to execute the method of automatedly building an inference path in a knowledge base comprising a representation of a model of a domain as objects and links arranged in an oriented bipartite graph, wherein the objects include parameters, and the links include rules, and wherein each rule has at least one input variable and at least one output variable, and each parameter associated with a rule is either an input variable or an output variable of the rule; said method comprising: generating a collection of known parameters and specifying one or more required parameters; performing processing with respect to each known parameter which has not undergone said processing before, in order to find the required parameters, said processing comprising: determining launchable rules wherein: the known parameter is an input variable in the launchable rules, all remaining input variables are known for the launchable rules, and the launchable rules have not been launched before; simultaneously launching multiple said determined launchable rules and adding output variables of the launched rules to the collection of known parameters, and carrying out analysis regarding achievement of a goal, wherein simulation of launching a rule is performed by assigning values “known” to variables outputted in said rule; and if all the required parameters are found, terminating the processing and identifying a problem as solved; otherwise, performing subsequent search for the inference path; and building a sequence of the launched rules in an order in which they were launched, the built sequence of rules representing the inference path.