Goren Gordon

When encountering novel environments, animals perform complex yet structured exploratory behaviors. Despite their typical structuring, the principles underlying exploratory patterns are still not sufficiently understood. Here we analyzed exploratory behavioral data from two modalities: whisking and locomotion in rats and mice. We found that these rodents maximized novelty signal-to-noise ratio during each exploration episode, where novelty is defined as the accumulated information gain. We further found that these rodents maximized novelty during outbound exploration, used novelty-triggered withdrawal-like retreat behavior, and explored the environment in a novelty-descending sequence. We applied a hierarchical curiosity model, which incorporates these principles, to both modalities. We show that the model captures the major components of exploratory behavior in multiple timescales: single excursions, exploratory episodes, and developmental timeline. The model predicted that novelty...

Entanglement is very susceptible to decoherence and can rapidly decay or even completely disappear in finite time. A universal dynamical control of the disentanglement approach is presented, whereby one locally modulates entangled systems weakly coupled to thermal baths. We show that these local modulations can reduce the entanglement's decay rate and may facilitate controlled oscillations of entanglement that result in entanglement partial resuscitation. In the case of separate systems, we show that controlling the asymmetry between the systems' decoherence rates may result in partial resuscitation in non-Markovian time scales. Furthermore, controlling the time-dependent cross-decoherence of systems coupled to the same bath may exhibit partial resuscitation on longer time scales, dictated by the local modulations.

A unified theory is given of dynamically modified decay and decoherence of field-driven multilevel multipartite entangled states that are weakly coupled to zero-temperature baths. The theory allows for arbitrary local differences in their coupling to the environment. Due to such differences, the optimal driving-field modulation to ensure maximal fidelity is found to substantially differ from conventional pi-phase flips of the single-qubit evolution.

ABSTRACT We present an approach to monitoring and controlling a free quantum particle by coupling an internal (discrete) state of the particle to a detector (or probe). We consider a sequence of time-dependent, spatially localized interactions of the particle with the probe that are purely coherent (nondissipative), without mean energy-momentum exchange. We show that a sequence of such force-free interactions can freeze or deflect the particle.

ABSTRACT We investigate the scaling of decoherence rates and their dynamical suppression with the number N of qubits in various entangled states. Remarkably, for sufficiently large N, coherence time is always in the Zeno regime. This changes the scaling to the square root of the Markov-regime scaling. We find that a simple and effective control strategy is to locally modulate the individual qubits and thereby not only suppress the decoherence rate of each qubit, but also reduce the decoherence scaling of entangled states that are particularly fragile, from N2 to N, resulting in a dramatic reduction of the decoherence (by orders of magnitude). Surprisingly, the conditions for the effectiveness of such decoherence control are independent of N.

Rats move their whiskers to acquire information about their environment. It has been observed that they palpate novel objects and objects they are required to localize in space. We analyze whisker-based object localization using two complementary paradigms, namely, active learning and intrinsic-reward reinforcement learning. Active learning algorithms select the next training samples according to the hypothesized solution in order to better discriminate between correct and incorrect labels. Intrinsic-reward reinforcement learning uses prediction errors as the reward to an actor-critic design, such that behavior converges to the one that optimizes the learning process. We show that in the context of object localization, the two paradigms result in palpation whisking as their respective optimal solution. These results suggest that rats may employ principles of active learning and/or intrinsic reward in tactile exploration and can guide future research to seek the underlying neuronal mechanisms that implement them. Furthermore, these paradigms are easily transferable to biomimetic whisker-based artificial sensors and can improve the active exploration of their environment.

Animals explore novel environments in a cautious manner, exhibiting alternation between curiosity-driven behavior and retreats. We present a detailed formal framework for exploration behavior, which generates behavior that maintains a constant level of novelty. Similar to other types of complex behaviors, the resulting exploratory behavior is composed of exploration motor primitives. These primitives can be learned during a developmental period, wherein the agent experiences repeated interactions with environments that share common traits, thus allowing transference of motor learning to novel environments. The emergence of exploration motor primitives is the result of reinforcement learning in which information gain serves as intrinsic reward. Furthermore, actors and critics are local and ego-centric, thus enabling transference to other environments. Novelty control, i.e. the principle which governs the maintenance of constant novelty, is implemented by a central action-selection mechanism, which switches between the emergent exploration primitives and a retreat policy, based on the currently-experienced novelty. The framework has only a few parameters, wherein time-scales, learning rates and thresholds are adaptive, and can thus be easily applied to many scenarios. We implement it by modeling the rodent's whisking system and show that it can explain characteristic observed behaviors. A detailed discussion of the framework's merits and flaws, as compared to other related models, concludes the paper.