A model of user behaviour based automated planning is introduced in this work. The behaviour of u... more A model of user behaviour based automated planning is introduced in this work. The behaviour of users of web interactive systems can be described in term of a planning domain encapsulating the timed actions patterns representing the intended user profile. The user behaviour recognition is then posed as a planning problem where the goal is to parse a given sequence of user logs of the observed activities while reaching a final state. A general technique for transforming a timed finite state automata description of the behaviour into a numerical parameter planning model is introduced. Experimental results show that the performance of a planning based behaviour model is effective and scalable for real world applications. A major advantage of the planning based approach is to represent in a single automated reasoning framework problems of plan recognitions, plan synthesis and plan optimisation.
In this paper it has been verified, by a computer-based proof, that the smallest size of a comple... more In this paper it has been verified, by a computer-based proof, that the smallest size of a complete arc is 14 in PG(2,31) and in PG(2,32). Some examples of such arcs are also described. Comment: 6pages
2015 15th International Conference on Computational Science and Its Applications, 2015
ABSTRACT Most of the best performing link prediction ranking measures evaluate the common neighbo... more ABSTRACT Most of the best performing link prediction ranking measures evaluate the common neighbourhood of a pair of nodes in a network, in order to assess the likelihood of a new link. On the other hand, the same zero rank value is given to node pairs with no common neighbourhood, which usually are a large number of potentially new links, thus resulting in very low quality overall link ranking in terms of average edit distance to the optimal rank. In this paper we introduce a general technique for improving the quality of the ranking of common neighbours-based measures. The proposed method iteratively applies any given ranking measure to the quasi-common neighbours of the node pair. Experiments held on widely accepted datasets show that QCNAA, a quasi-common neighbourhood measure derived from the well know Adamic- Adar (AA), generates rankings which generally improve the ranking quality, while maintaining the prediction capability of the original AA measure.
This paper presents theoretical results and techniques for representing and managing task network... more This paper presents theoretical results and techniques for representing and managing task network goals in the framework of partial order planning. Task oriented formalisms are more expressive than partial order based formalism for problem goals in dynamical and changing domains, but they are not more powerful. We prove that it is always possible to express a task network problem in terms of an equivalent problem stated in partial order planning formalism. The task network model has been extended to describe external events (EETN), a feature not present in many planning models. The equivalence between this new model and PO formalism is also proved. These results allow to reuse existing partial order planners as tools in order to solve task network goals. We introduce a linear cost technique of domain transformation which compiles a given task domain in an equivalent operator based domain which is then submitted to a nonlinear planner. This technique has been successfully demonstrated by the implementation of a EETN planner based on domain tranformations for UCPOP.
ABSTRACT In this paper we show an approach to conditional planning which is based on a particular... more ABSTRACT In this paper we show an approach to conditional planning which is based on a particular three valued logic. Assignments and conditional formulae (built by means of the alternate operator as introduced in [7]) are used to represent uncertain situations. A model for actions in a conditional framework is defined by giving an execution function, which returns the updated situation after the execution, and an executability predicate. We also define a weakest precondition semantics in order to determine the least alternative situation in which a plan is executable and, after the execution, a required formula holds. The tools we introduced allow us to compile a plan in a macroaction, which is an abstraction of a plan, neglecting its internal decomposition. It is possible to prove that the use of macroactions is correct in a more complex plan.
2006 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Workshops, 2006
ABSTRACT In this work we introduce an adaptive architecture for supporting news information servi... more ABSTRACT In this work we introduce an adaptive architecture for supporting news information services in a dynamical web environment. In the news provider problem, a system continuously generates service instances (e.g.the news of a online newspaper) which should meet the requirements of a market of readers/agents which are supposed unknown. The only way for the system to know the evaluation of a service instance, i.e. a newspaper instance, is the feedback obtained after delivering it to the reader. In a dynamical environment the domain of the service offered is changing and the readers/agents are changing their preferences over the time. The proposed algorithm for newpapers production employs typical genetic operators in order to optimize the product delivered and to adapt it to the environment feedback and domain evolution. Experiments shows the capability of dynamical adaptation of the algorithm..
2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, 2009
In this paper we propose an approach to optimization of web marketing content based on online dis... more In this paper we propose an approach to optimization of web marketing content based on online discrete particle swarm optimization (PSO) model. The idea behind online PSO is to evaluate the collective user feedback as the PSO objective function which drive particles velocities in the hybrid continuous-discrete space of web content features. The PSO coordinate the process of sampling collective
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation, 2011
Differential Evolution (DE) is a popular and efficient optimization technique for real-valued spa... more Differential Evolution (DE) is a popular and efficient optimization technique for real-valued spaces based on the concepts of Darwinian evolution. Its main peculiarity is the use of a differential mutation operator that allows DE to automatically adjust the exploration/exploitation balance of its search moves. The major DE drawback is the need of a preliminary tuning of some numerical parameters. Although, recently some parameters adaptive schemes have been proposed, none of these takes into account the side effects introduced by changing two or more parameters at the same time. In this paper we introduce a DE self-adaptive scheme that takes into account the parameters dependencies by means of a multivariate probabilistic technique based on an Estimation of Distribution Algorithm working on the parameters space. Experiments have been performed on a set of commonly adopted benchmark problems and the obtained results show the competitiveness of our approach with respect to other adaptive DE schemes. Moreover, our scheme could be potentially adopted not only in DE but also in any other Evolutionary Algorithm or meta-heuristic technique presenting parameters that regulate the behavior of the search.
2009 IEEE International Conference on e-Business Engineering, 2009
In this paper we propose an approach to optimization of web marketing content based on an online ... more In this paper we propose an approach to optimization of web marketing content based on an online particle swarm optimization (PSO) model. The idea behind online PSO is to evaluate the collective user feedback as the PSO objective function which drives particles velocities in the hybrid continuous-discrete space of web content features. PSO coordinates the process of sampling collective user behavior in order to optimize the web marketing metric. To improve the performances a variation to the PSO schema is adopted, this variation consists in a restart of the algorithm if the convergence speed is not good. Experiments in the scenario of the home page of an online shop show that the method converges faster and avoid some common drawbacks such as local optimal and hybrid discrete/continuous features management; however is observed that the restart procedure improves the convergence speed of some difficult instances of the problem without affects the other ones. The proposed online optimization method is general and can be applied to other web marketing or business intelligent contexts.
The gray levels quantization technique is used to generate images which limit the number of color... more The gray levels quantization technique is used to generate images which limit the number of color levels resulting in a reduction of the image size, while it preserves the quality perceived by human observers. The problem is very relevant for image storage and web distribution, as well as in the case of devices with limited bandwidth, storage and/or computational capabilities.
A reason maintenance system which extends an ATMS through Mukaidono's fuzzy ... more A reason maintenance system which extends an ATMS through Mukaidono's fuzzy logic is described. It supports a problem solver in situations affected by incomplete information and vague data, by allowing nonmonotonic inferences and the revision of previous conclusions when contradictions are detected.
A reason maintenance system which extends an ATMS through Mukaidono's fuzzy logic is described. I... more A reason maintenance system which extends an ATMS through Mukaidono's fuzzy logic is described. It supports a problem solver in situations affected by incomplete information and vague data, by allowing nonmonotonic inferences and the revision of previous conclusions when contradictions are detected.
Particle Swarm Optimization (PSO) is a popular optimization technique based on swarm intelligence... more Particle Swarm Optimization (PSO) is a popular optimization technique based on swarm intelligence concepts. Estimation of Distribution Algorithms (EDAs) are a relatively new class of evolutionary algorithms which build a probabilistic model of the population dynamics and use this model to sample new individuals. Recently, the hybridization of PSO and EDAs is emerged as a new research trend. In this
2008 Third International Conference on Convergence and Hybrid Information Technology, 2008
A framework for online user behavior soft modeling is presented in this work. Behavior models of ... more A framework for online user behavior soft modeling is presented in this work. Behavior models of users in dynamic virtual environments has been described in the literature in terms of timed transition automata which can be compiled in a planning domain. The extended notion of soft timed transition automata is proposed in order to recognize a larger class of user
2008 IEEE International Conference on e-Business Engineering, 2008
A framework for online user behavior soft modeling is presented in this work. Behavior models of ... more A framework for online user behavior soft modeling is presented in this work. Behavior models of users in dynamic virtual environments has been described in the literature in terms of timed transition automata which can be compiled in a planning domain. The extended notion of soft timed transition automata is proposed in order to recognize a larger class of user histories. The notion of deviation from the user model allows to assess and evaluate in real time the dynamic behavior of users acting in virtual environments, such as e-learning and e-business platforms. The timed automata model allows to describe virtually infinite sequences of user actions subject to temporal constraints, while soft measures allows to assess recognition of behaviors by evaluating the amount of temporal deviation, additional or omitted actions contained in an observed behavior. The proposed model allow the partial recognition of user history also when the observed actions only partially meets the given behavior model constraints. This approach is more realistic for real time user support systems, with respect to standard boolean model recognition, when more than one user model is potentially available the amount of deviation from the models can be used as guide to generate the system support by anticipation, projection and other known techniques. Experiments based on logs from an e-learning platforms and plan compilation of the soft timed automaton shows the expressivity of the proposed model.
In this paper it has been verified, by an exhaustive computer search, that in PG(2, 25) the small... more In this paper it has been verified, by an exhaustive computer search, that in PG(2, 25) the smallest size of a complete arc is 12 and that complete 19-arcs and 20-arcs do not exist. Therefore, the spectrum of the sizes of the complete arcs in PG(2, 25) is completely determined. The classification of the smallest complete arcs is also given: the number of non-equivalent complete 12-arcs is 606 and for each of them the automorphism group has been found and some geometrical properties have been studied. The exhaustive search has been feasible because projective equivalence properties have been exploited to prune the search tree and to avoid generating too many isomorphic copies of the same arc.
In this paper we determine the largest size of a complete (n; 3)-arc in PG(2,11). By a computer-b... more In this paper we determine the largest size of a complete (n; 3)-arc in PG(2,11). By a computer-based exhaustive search that exploits the fact that an (n; 3)-arc with n¿21 contains an arc of size 7 and that uses projective equivalence properties, we show that the largest size of an (n; 3)-arc in PG(2,11) is 21 and that only two non-equivalent (21; 3)-arcs exist.
The diffusion of domotic and ambient intelligence systems have introduced a new vision in which a... more The diffusion of domotic and ambient intelligence systems have introduced a new vision in which autonomous deliberative agents operate in environments where reactive responses of devices can be cooperatively exploited to fulfill the agent's goals. In this article a model for automated planning in reactive environments, based on numerical planning, is introduced. A planner system, based on mixed integer linear programming techniques, which implements the model, is also presented. The planner is able to reason about the dynamic features of the environment and to produce solution plans, which take into account reactive devices and their causal relations with agent's goals by exploitation and avoidance techniques, to reach a given goal state. The introduction of reactive domains in planning poses some issues concerning reasoning patterns which are briefly depicted. Experiments of planning in reactive domains are also discussed.
A model of user behaviour based automated planning is introduced in this work. The behaviour of u... more A model of user behaviour based automated planning is introduced in this work. The behaviour of users of web interactive systems can be described in term of a planning domain encapsulating the timed actions patterns representing the intended user profile. The user behaviour recognition is then posed as a planning problem where the goal is to parse a given sequence of user logs of the observed activities while reaching a final state. A general technique for transforming a timed finite state automata description of the behaviour into a numerical parameter planning model is introduced. Experimental results show that the performance of a planning based behaviour model is effective and scalable for real world applications. A major advantage of the planning based approach is to represent in a single automated reasoning framework problems of plan recognitions, plan synthesis and plan optimisation.
In this paper it has been verified, by a computer-based proof, that the smallest size of a comple... more In this paper it has been verified, by a computer-based proof, that the smallest size of a complete arc is 14 in PG(2,31) and in PG(2,32). Some examples of such arcs are also described. Comment: 6pages
2015 15th International Conference on Computational Science and Its Applications, 2015
ABSTRACT Most of the best performing link prediction ranking measures evaluate the common neighbo... more ABSTRACT Most of the best performing link prediction ranking measures evaluate the common neighbourhood of a pair of nodes in a network, in order to assess the likelihood of a new link. On the other hand, the same zero rank value is given to node pairs with no common neighbourhood, which usually are a large number of potentially new links, thus resulting in very low quality overall link ranking in terms of average edit distance to the optimal rank. In this paper we introduce a general technique for improving the quality of the ranking of common neighbours-based measures. The proposed method iteratively applies any given ranking measure to the quasi-common neighbours of the node pair. Experiments held on widely accepted datasets show that QCNAA, a quasi-common neighbourhood measure derived from the well know Adamic- Adar (AA), generates rankings which generally improve the ranking quality, while maintaining the prediction capability of the original AA measure.
This paper presents theoretical results and techniques for representing and managing task network... more This paper presents theoretical results and techniques for representing and managing task network goals in the framework of partial order planning. Task oriented formalisms are more expressive than partial order based formalism for problem goals in dynamical and changing domains, but they are not more powerful. We prove that it is always possible to express a task network problem in terms of an equivalent problem stated in partial order planning formalism. The task network model has been extended to describe external events (EETN), a feature not present in many planning models. The equivalence between this new model and PO formalism is also proved. These results allow to reuse existing partial order planners as tools in order to solve task network goals. We introduce a linear cost technique of domain transformation which compiles a given task domain in an equivalent operator based domain which is then submitted to a nonlinear planner. This technique has been successfully demonstrated by the implementation of a EETN planner based on domain tranformations for UCPOP.
ABSTRACT In this paper we show an approach to conditional planning which is based on a particular... more ABSTRACT In this paper we show an approach to conditional planning which is based on a particular three valued logic. Assignments and conditional formulae (built by means of the alternate operator as introduced in [7]) are used to represent uncertain situations. A model for actions in a conditional framework is defined by giving an execution function, which returns the updated situation after the execution, and an executability predicate. We also define a weakest precondition semantics in order to determine the least alternative situation in which a plan is executable and, after the execution, a required formula holds. The tools we introduced allow us to compile a plan in a macroaction, which is an abstraction of a plan, neglecting its internal decomposition. It is possible to prove that the use of macroactions is correct in a more complex plan.
2006 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Workshops, 2006
ABSTRACT In this work we introduce an adaptive architecture for supporting news information servi... more ABSTRACT In this work we introduce an adaptive architecture for supporting news information services in a dynamical web environment. In the news provider problem, a system continuously generates service instances (e.g.the news of a online newspaper) which should meet the requirements of a market of readers/agents which are supposed unknown. The only way for the system to know the evaluation of a service instance, i.e. a newspaper instance, is the feedback obtained after delivering it to the reader. In a dynamical environment the domain of the service offered is changing and the readers/agents are changing their preferences over the time. The proposed algorithm for newpapers production employs typical genetic operators in order to optimize the product delivered and to adapt it to the environment feedback and domain evolution. Experiments shows the capability of dynamical adaptation of the algorithm..
2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, 2009
In this paper we propose an approach to optimization of web marketing content based on online dis... more In this paper we propose an approach to optimization of web marketing content based on online discrete particle swarm optimization (PSO) model. The idea behind online PSO is to evaluate the collective user feedback as the PSO objective function which drive particles velocities in the hybrid continuous-discrete space of web content features. The PSO coordinate the process of sampling collective
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation, 2011
Differential Evolution (DE) is a popular and efficient optimization technique for real-valued spa... more Differential Evolution (DE) is a popular and efficient optimization technique for real-valued spaces based on the concepts of Darwinian evolution. Its main peculiarity is the use of a differential mutation operator that allows DE to automatically adjust the exploration/exploitation balance of its search moves. The major DE drawback is the need of a preliminary tuning of some numerical parameters. Although, recently some parameters adaptive schemes have been proposed, none of these takes into account the side effects introduced by changing two or more parameters at the same time. In this paper we introduce a DE self-adaptive scheme that takes into account the parameters dependencies by means of a multivariate probabilistic technique based on an Estimation of Distribution Algorithm working on the parameters space. Experiments have been performed on a set of commonly adopted benchmark problems and the obtained results show the competitiveness of our approach with respect to other adaptive DE schemes. Moreover, our scheme could be potentially adopted not only in DE but also in any other Evolutionary Algorithm or meta-heuristic technique presenting parameters that regulate the behavior of the search.
2009 IEEE International Conference on e-Business Engineering, 2009
In this paper we propose an approach to optimization of web marketing content based on an online ... more In this paper we propose an approach to optimization of web marketing content based on an online particle swarm optimization (PSO) model. The idea behind online PSO is to evaluate the collective user feedback as the PSO objective function which drives particles velocities in the hybrid continuous-discrete space of web content features. PSO coordinates the process of sampling collective user behavior in order to optimize the web marketing metric. To improve the performances a variation to the PSO schema is adopted, this variation consists in a restart of the algorithm if the convergence speed is not good. Experiments in the scenario of the home page of an online shop show that the method converges faster and avoid some common drawbacks such as local optimal and hybrid discrete/continuous features management; however is observed that the restart procedure improves the convergence speed of some difficult instances of the problem without affects the other ones. The proposed online optimization method is general and can be applied to other web marketing or business intelligent contexts.
The gray levels quantization technique is used to generate images which limit the number of color... more The gray levels quantization technique is used to generate images which limit the number of color levels resulting in a reduction of the image size, while it preserves the quality perceived by human observers. The problem is very relevant for image storage and web distribution, as well as in the case of devices with limited bandwidth, storage and/or computational capabilities.
A reason maintenance system which extends an ATMS through Mukaidono's fuzzy ... more A reason maintenance system which extends an ATMS through Mukaidono's fuzzy logic is described. It supports a problem solver in situations affected by incomplete information and vague data, by allowing nonmonotonic inferences and the revision of previous conclusions when contradictions are detected.
A reason maintenance system which extends an ATMS through Mukaidono's fuzzy logic is described. I... more A reason maintenance system which extends an ATMS through Mukaidono's fuzzy logic is described. It supports a problem solver in situations affected by incomplete information and vague data, by allowing nonmonotonic inferences and the revision of previous conclusions when contradictions are detected.
Particle Swarm Optimization (PSO) is a popular optimization technique based on swarm intelligence... more Particle Swarm Optimization (PSO) is a popular optimization technique based on swarm intelligence concepts. Estimation of Distribution Algorithms (EDAs) are a relatively new class of evolutionary algorithms which build a probabilistic model of the population dynamics and use this model to sample new individuals. Recently, the hybridization of PSO and EDAs is emerged as a new research trend. In this
2008 Third International Conference on Convergence and Hybrid Information Technology, 2008
A framework for online user behavior soft modeling is presented in this work. Behavior models of ... more A framework for online user behavior soft modeling is presented in this work. Behavior models of users in dynamic virtual environments has been described in the literature in terms of timed transition automata which can be compiled in a planning domain. The extended notion of soft timed transition automata is proposed in order to recognize a larger class of user
2008 IEEE International Conference on e-Business Engineering, 2008
A framework for online user behavior soft modeling is presented in this work. Behavior models of ... more A framework for online user behavior soft modeling is presented in this work. Behavior models of users in dynamic virtual environments has been described in the literature in terms of timed transition automata which can be compiled in a planning domain. The extended notion of soft timed transition automata is proposed in order to recognize a larger class of user histories. The notion of deviation from the user model allows to assess and evaluate in real time the dynamic behavior of users acting in virtual environments, such as e-learning and e-business platforms. The timed automata model allows to describe virtually infinite sequences of user actions subject to temporal constraints, while soft measures allows to assess recognition of behaviors by evaluating the amount of temporal deviation, additional or omitted actions contained in an observed behavior. The proposed model allow the partial recognition of user history also when the observed actions only partially meets the given behavior model constraints. This approach is more realistic for real time user support systems, with respect to standard boolean model recognition, when more than one user model is potentially available the amount of deviation from the models can be used as guide to generate the system support by anticipation, projection and other known techniques. Experiments based on logs from an e-learning platforms and plan compilation of the soft timed automaton shows the expressivity of the proposed model.
In this paper it has been verified, by an exhaustive computer search, that in PG(2, 25) the small... more In this paper it has been verified, by an exhaustive computer search, that in PG(2, 25) the smallest size of a complete arc is 12 and that complete 19-arcs and 20-arcs do not exist. Therefore, the spectrum of the sizes of the complete arcs in PG(2, 25) is completely determined. The classification of the smallest complete arcs is also given: the number of non-equivalent complete 12-arcs is 606 and for each of them the automorphism group has been found and some geometrical properties have been studied. The exhaustive search has been feasible because projective equivalence properties have been exploited to prune the search tree and to avoid generating too many isomorphic copies of the same arc.
In this paper we determine the largest size of a complete (n; 3)-arc in PG(2,11). By a computer-b... more In this paper we determine the largest size of a complete (n; 3)-arc in PG(2,11). By a computer-based exhaustive search that exploits the fact that an (n; 3)-arc with n¿21 contains an arc of size 7 and that uses projective equivalence properties, we show that the largest size of an (n; 3)-arc in PG(2,11) is 21 and that only two non-equivalent (21; 3)-arcs exist.
The diffusion of domotic and ambient intelligence systems have introduced a new vision in which a... more The diffusion of domotic and ambient intelligence systems have introduced a new vision in which autonomous deliberative agents operate in environments where reactive responses of devices can be cooperatively exploited to fulfill the agent's goals. In this article a model for automated planning in reactive environments, based on numerical planning, is introduced. A planner system, based on mixed integer linear programming techniques, which implements the model, is also presented. The planner is able to reason about the dynamic features of the environment and to produce solution plans, which take into account reactive devices and their causal relations with agent's goals by exploitation and avoidance techniques, to reach a given goal state. The introduction of reactive domains in planning poses some issues concerning reasoning patterns which are briefly depicted. Experiments of planning in reactive domains are also discussed.
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Papers by Alfredo Milani