Abstract: An apparatus and method for machine-updating of prototypes—for example, during design of digital objects, or content-management—has input means (15) for inputting descriptive classifiers (tags) that a user assigns to prototypes and a tag model generator (20) that uses machine learning techniques to produce a model of the association between the assigned tags and the values of quantifiable, non-subjective attributes of the tagged prototypes. In order to obtain a desired updating of a current prototype, the user issues a command which defines the desired variation of the current prototype by referring to one or more conditions that should be met by specified tags of the updated prototype. The prototype-updating apparatus/method has a prototype updater (30) that identifies a suitable updated prototype whose tags meet the condition(s) specified in the user's command and which, globally, is fairly similar to the pre-update prototype.

Abstract: Meta-data (tags) for an audiovisual file can be generated by producing an initial estimate of the tags and then revising the estimate (notably to expand it and/or render it more precise) based on the assumption that the relationships which hold between the different tags for a set of manually-tagged training examples will also hold for the tags of the input file now being tagged. A fully-automatic method and system is a hybrid between signal-based and machine-learning approaches, because the initial tag estimate is based on the physical properties of the signal representing the audiovisual file. The initial tag estimate may be produced by inferring that the input content will have the same tags as those files of the same kind, in the training database, which have a global similarity to the input audiovisual file in terms of signal properties.

Abstract: Meta-data (tags) for an audiovisual file can be generated by prompting a user to input certain tags (meta-data) descriptive of the audiovisual file, to serve as an initial estimate of the tags, and then revising the initial estimate (notably to expand it and/or render it more precise) based on the assumption that the relationships which hold between the different tags for a set of manually-tagged training examples will also hold for the tags of the input file now being tagged.

Abstract: Multiple parallel signal streams are produced by the sensors (20, 30, 40, 50) associated with a device (10). Events corresponding to real-world activities, contexts, environments, internal-states, uses, interactions and the like involving the device (10) can be detected in the multi-channel sensor-signal stream by evaluating how the pattern of coordination between the different sensors varies over time. The pattern of coordination between the sensors can be evaluated for a particular time period by computing an information distance matrix (IDM) for the sensor-signals generated during that time period. The IDM summarizes the normalized information distance between each possible pairing of the sensors.

Abstract: A content-management interface is implemented using superposition of graphical “widget” elements onto an on-screen display of the real-time image of a user. The widgets are motion-sensitive control elements which are responsive to user movement that produces motion of the user's displayed image at an on-screen location associated with that widget. The user can operate the widget virtually, for example by moving his hand over a widget, or pushing a widget along. Meta-data descriptive of the content to be managed is mapped onto widgets, enabling the user to interact with the meta-data, notably by changing it or by selecting content with reference to it.

Abstract: An apparatus and method for machine-updating of prototypes—for example, during design of digital objects, or content-management—has input means (15) for inputting descriptive classifiers (tags) that a user assigns to prototypes and a tag model generator (20) that uses machine learning techniques to produce a model of the association between the assigned tags and the values of quantifiable, non-subjective attributes of the tagged prototypes. In order to obtain a desired updating of a current prototype, the user issues a command which defines the desired variation of the current prototype by referring to one or more conditions that should be met by specified tags of the updated prototype. The prototype-updating apparatus/method has a prototype updater (30) that identifies a suitable updated prototype whose tags meet the condition(s) specified in the user's command and which, globally, is fairly similar to the pre-update prototype.

Abstract: The invention relates to a hand tool machine, particularly a drill and/or chisel hammer, having a striking unit comprising at least one hammer and one striking element, and having a damping device for the striking element for damping a B-strike of the striking element against a striking unit. The invention proposes that the damping device have at least one axial overlap region with the hammer in at least one operating mode.

Abstract: A set of temporal phases are defined, occurring successively during the playback of music (or other content) to a user. Each temporal phase is associated with a set of selection criteria. If the user operates a selection device (which can be a computer mouse button) while a piece of music or other content is being played back, the selection phase applicable at the time of user-action is determined and further content is selected based on the selection criteria associated with the applicable phase. This enables the user, with minimal action, to influence the content being rendered. The selection criteria can be related to the meta-data of the content being played back at the time of user action. The meaning attributed to the applicable temporal phase can be varied depending on the pressure of the mouse button click.

Abstract: Meta-data (tags) for an audiovisual file can be generated by prompting a user to input certain tags (meta-data) descriptive of the audiovisual file, to serve as an initial estimate of the tags, and then revising the initial estimate (notably to expand it and/or render it more precise) based on the assumption that the relationships which hold between the different tags for a set of manually-tagged training examples will also hold for the tags of the input file now being tagged.

Abstract: Audio samples corresponding to audio extracts or whole audio titles are automatically mapped to triggers 12 in a playable sound-producing device 1, the mapping being dependent on the meta-data associated with the audio samples. Thus, a user can play the sound-producing device and generate sounds derived from his favorite audio titles. It is possible to define different mappings between the audio samples and the playable domain of the sound-producing device: an audio sample selector 50 can select between different possible samples for playback by comparing the audio properties of the samples and the play-mode and/or characteristics of the user's performance. An audio sampler/sample-processor 70 can automatically extract segments of an audio source file and map them to triggers in the sound-producing device 1.

Abstract: In the exchange of information in a peer-to-peer information system network, the problem of semantic interoperability of the communication system used by the agent associated with every peer is addressed not by imposing a universal pre-defined ontology over universally defined conceptual schemata, but instead using mechanisms, inspired from natural language, that enable each agent to develop a repertoire of grounded categories and labels for these categories and to negotiate their use and semantics with other agents. The communication system, as well as its semantics, is hence emergent and adaptive instead of predefined.

Abstract: In order to promote efficient learning of relationships inherent in a system or setup S described by system-state and context parameters, the next action to take, affecting the setup, is determined based on the knowledge gain expected to result from this action. Knowledge-gain is assessed “locally” by comparing the value of a knowledge-indicator parameter after the action with the value of this indicator on one or more previous occasions when the system-state/context parameter(s) and action variable(s) had similar values to the current ones. Preferably the “level of knowledge” is assessed based on the accuracy of predictions made by a prediction module. This technique can be applied to train a prediction machine by causing it to participate in the selection of a sequence of actions. This technique can also be applied for managing development of a self-developing device or system, the self-developing device or system performing a sequence of actions selected according to the action-selection technique.

Abstract: Multiple parallel signal streams are produced by the sensors (20,30,40,50) associated with a device (10). Events corresponding to real-world activities, contexts, environments, internal-states, uses, interactions and the like involving the device (10) can be detected in the multi-channel sensor-signal stream by evaluating how the pattern of coordination between the different sensors varies over time. The pattern of coordination between the sensors can be evaluated for a particular time period by computing an information distance matrix (IDM) for the sensor-signals generated during that time period. The IDM summarizes the normalized information distance between each possible pairing of the sensors.

Abstract: The invention enables to generate a general function (4) which can operate on an input signal (Sx) to extract from the latter a value (DVex) of a global characteristic value expressing a feature (De) of the information conveyed by that signal. It operates by: generating at least one compound function (CF1-CFn), said compound function being generated from at least one of a set of elementary functions (EF1, EF2, . . .

Abstract: In a system and method for facilitating wireless communication between agents in a wireless network, each agent is equipped with an agent's device using a main wireless infrastructure and a separate auxiliary wireless infrastructure. Initial contact between any first agent's device and any other agent's device is made within the auxiliary wireless infrastructure, whereas, once this initial contact has been established, all ensuing communications between the first agent's device and the other agent's device take place within the main wireless infrastructure.

Abstract: Multiple parallel signal streams are produced by the sensors (20, 30, 40, 50) associated with a device (10). Events corresponding to real-world activities, contexts, environments, internal-states, uses, interactions and the like involving the device (10) can be detected in the multi-channel sensor-signal stream by evaluating how the pattern of coordination between the different sensors varies over time. The pattern of coordination between the sensors can be evaluated for a particular time period by computing an information distance matrix (IDM) for the sensor-signals generated during that time period. The IDM summarizes the normalized information distance between each possible pairing of the sensors.

Abstract: In a system and method for facilitating wireless communication between agents in a wireless network, each agent is equipped with an agent's device (10a, 10b) using a main wireless infrastructure (2) and a separate auxiliary wireless infrastructure (1). Initial contact between any first agent's device (10a) and any other agent's device (10b) is made within the auxiliary wireless infrastructure, whereas, once this initial contact has been established, all ensuing communications between the first agent's device (10a) and the other agent's device (10b) take place within the main wireless infrastructure.

Abstract: The adaptive artificial vision method comprises the following steps: (a) defining successive couples of timesteps (t?1, t; t, t+1; . . . ) synchronized by a clock (101), (b) comparing two successive images (It?, It; It, It+1, . . . ) from an input device (102, 103) at each couple of synchronized timesteps (t?1, t; t, t+1; . . . ) spaced by a predetermined time delay ?0 for obtaining a delta image ?t which is the result of the computation of the distance between each pixel of the two successive images (It?1, It; It, It+1, . . .

Abstract: A self-developing device (1) capable of open-ended development makes use of a special motivational system for selecting which action should be taken on the environment by an associated sensory-motor apparatus (2). For a given candidate action, a motivational module (11) calculates a reward associated with the corresponding values that would be taken by one or more motivational variables that are independent of the nature of the associated sensory-motor apparatus. Preferred motivational variables are dependent on the developmental history of the device (1), and include variables quantifying the predictability, familiarity and stability of sensory-motor variables serving as the inputs to the device (1). The sensory-motor variables represent the status of the external environment and/or the internal resources (3) of the sensory-motor apparatus (2) whose behavior is controlled by the self-developing device (1).

Abstract: Method and apparatus for controlling the operation of an emotion synthesizing device, notably of the type where the emotion is conveyed by a sound, having at least one input parameter whose value is used to set a type of emotion to be conveyed, by making at least one parameter a variable parameter over a determined control range, thereby to confer a variability in an amount of the type of emotion to be conveyed. The variable parameter can be made variable according to a variation model over the control range, the model relating a quantity of emotion control variable to the variable parameter, whereby said control variable is used to variably establish a value of said variable parameter. Preferably the variation obeys a linear model, the variable parameter being made to vary linearly with a variation in a quantity of emotion control variable.