The idea of dynamic move chains has been described in a preceding paper [10]. Re-using an earlier piece of search allows the tree to be forward-pruned, which is known to be dangerous, because it can potentially remove new information that would only be realised through a more exhaustive search process. The justification is the integrity in the position and small changes between positions make it more likely that an earlier result still applies. Larger problems where exhaustive search is not possible would also like a method that can guess accurately. This paper has added to the forward-pruning technique by using 'move tables' that can act in the same way as Transposition Tables, but for moves not positions. They use an efficient memory structure and have put the design into the context of short or long-term memories. The long-term memory includes simply rote-learning of other players' games. The forward-pruning technique can also be fortified to help to remove some potential errors. Another idea is 'long branches'. This plays a short move sequence, before returning to a full search at the resulting leaf nodes. Therefore, with some configuration the dynamic tables can be reliably used and relatively independently of the position. This has advanced some of the future work theory of the earlier paper, and made more explicit where logical plans and more knowledge-based approaches might be applied. The author would argue that the process is a very human approach to searching for chess moves.

With the inexorable expansion of the semantic layer on the Web and its ecosystem of connected applications, the global citizens expect more and more data expositions coming from public activities. The recent developments in knowledge representation and reasoning push public structures to deploy their data warehouses in parallel of classical websites exhibitions. This article presents an infrastructure to spread the descriptions of scholarships. After introducing the major contributions concerning the semantical annotation of materials occurring in recruitment processes, we describe our case study about the strategy of the University of Sassari concerning the expositions of academical grants. Supported by a core and aligned ontology of the domain we present our prototypical architecture to support and gather the spread of scholarships.

The aim of process discovery, originating from the area of process mining, is to discover a process model based on business process execution data. A majority of process discovery techniques relies on an event log as an input. An event log is a static source of historical data capturing the execution of a business process. In this paper we focus on process discovery relying on online streams of business process execution events. Learning process models from event streams poses both challenges and opportunities, i.e. we need to handle unlimited amounts of data using finite memory and, preferably, constant time. We propose a generic architecture that allows for adopting several classes of existing process discovery techniques in context of event streams. Moreover, we provide several instantiations of the architecture, accompanied by implementations in the process mining tool-kit ProM (http://promtools.org). Using these instantiations, we evaluate several dimensions of stream-based process discovery. The evaluation shows that the proposed architecture allows us to lift process discovery to the streaming domain.

House finches based in North American cities and town are better at solving problems than rural ones. Researchers investigated how increased urbanization and human presence affects the behavior and foraging habits of birds. The findings suggests that city birds have become used to humans, but rural birds have not, so they perceive humans as threatening, interfering with their ability to problem solve. The house finch (Haemorhous mexicanus) is a songbird native to the desert areas of North America. It's found in urban and rural areas in Mexico, as well as the southwestern United States.

Steve Miller Band's The Joker was on the FM dial and Mohammed Ali had trounced George Forman to regain his heavyweight title in the much hyped (if questionably named) Rumble in the Jungle. Inflation had reached double digit highs, gasoline was in short supply, President Richard Nixon stepped down in the wake of the Watergate Scandal, and a 29-year-old Hungarian architect by the name of Erno Rubik had finally figured out how he could take a block made of smaller blocks and get the smaller cubes to move without causing the whole structure to fall apart. And thus, the Rubik's cube, which would eventually go on to delight and torment millions, was born. Ostensible a toy, Rubik's cube has since been the subject of everything from high school math class experiments to serious research in computer science. This week, students at the University of Michigan did Rubik one better, building the world's largest freestanding cube and overcoming a design challenge not too dissimilar from Rubik's original quandry--how to get the cubes to spin.

Although an expert Rubik's player can solve the puzzle in seconds, the nature of this particular cube means that even the best player will need a lot more time to finish, according to cube co-developer Ryan Kuhn.

AI applications have been deployed and used for industrial, government, and consumer purposes for many years. The experiences have been documented in IAAI conference proceedings since 1989. Over the years, the breadth of applications has expanded many times over and AI systems have become more commonplace. Indeed, AI has recently become a focal point in the industrial and consumer consciousness. This article focuses on changes in the world of computing over the last three decades that made building AI applications more feasible. We then examine lessons learned during this time and distill these lessons into succinct advice for future application builders.

hakey the Robot, conceived fifty years ago, was a seminal contribution to AI. Shakey perceived its world, planned how to achieve a goal, and acted to carry out that plan. This was revolutionary. At the Twenty-Ninth AAAI Conference on Artificial Intelligence, attendees gathered to celebrate Shakey, and to gain insights into how the AI revolution moves ahead. The celebration included a panel, chaired by Benjamin Kuipers and featuring AI pioneers Ed Feigenbaum, Peter Hart, and Nils Nilsson. This article includes written versions of the contributions of those panelists.

"The remedy is more speech, not enforced silence," wrote US Supreme Court justice Louis Brandeis in 1927 in his defence of freedom of speech. Ninety years on, his position is often taken as read: in the marketplace of ideas, eventually the truth will out. So it's no surprise that many were aghast when, last week, Germany's justice minister introduced a draft law that would fine social media companies, including Facebook and Twitter, up to €50 million if they failed to remove hate speech within 24 hours of a complaint.

In this paper we look into the problem of planning over hybrid domains, where change can be both discrete and instantaneous, or continuous over time. In addition, it is required that each state on the trajectory induced by the execution of plans complies with a given set of global constraints. We approach the computation of plans for such domains as the problem of searching over a deterministic state model. In this model, some of the successor states are obtained by solving numerically the so-called initial value problem over a set of ordinary differential equations (ODE) given by the current plan prefix. These equations hold over time intervals whose duration is determined dynamically, according to whether zero crossing events take place for a set of invariant conditions. The resulting planner, FS+, incorporates these features together with effective heuristic guidance. FS+ does not impose any of the syntactic restrictions on process effects often found on the existing literature on Hybrid Planning. A key concept of our approach is that a clear separation is struck between planning and simulation time steps. The former is the time allowed to observe the evolution of a given dynamical system before committing to a future course of action, whilst the later is part of the model of the environment. FS+ is shown to be a robust planner over a diverse set of hybrid domains, taken from the existing literature on hybrid planning and systems.