objective(s) learning is defined as the acquisition of information and skills, while subsequent retention of that information is called memory. the objective of the present study was to investigate the effect of aqueous extract of boswellia papyrifera on learning and memory paradigms in mice and rats. materials and methods this study was held at the department of pharmacology, faculty of pharma...

This paper presents reinforcement learning with a Long Short-Term Memory recurrent neural network: RL-LSTM. Model-free RL-LSTM using Advantage( ) learning and directed exploration can solve non-Markovian tasks with long-term dependencies between relevant events. This is demonstrated in a T-maze task, as well as in a di cult variation of the pole balancing task.

This paper presents reinforcement learning with a Long ShortTerm Memory recurrent neural network: RL-LSTM. Model-free RL-LSTM using Advantage( ) learning and directed exploration can solve non-Markovian tasks with long-term dependencies between relevant events. This is demonstrated in a T-maze task, as well as in a di cult variation of the pole balancing task.

Instead of training a Neural Turing Machine (NTM) with gradient descent [1], in this work NTMs are trained through an evolutionary algorithm. Preliminary results suggest that this setup can greatly simplify the neural model, generalizes better, and does not require accessing the entire memory content at each time-step. We show preliminary results on a simple copy and T-Maze learning task.

Artificial Intelligence (AI) has always tried to emulate the greatest virtue of humans: their intelligence. However, although there have been many efforts to reach this goal, at a glance we notice that the intelligence of AI systems barely resembles that of humans. Today, available methods that assess AI systems are focused on using empirical techniques to measure the performance of algorithms ...

The Cell-DEVS formalism was created as an extension of cellular automata for modeling complex systems using a discrete event formal approach. We examine the application of the Cell-DEVS formalism to a maze-solving application. The model uses the CD++ toolkit to model and simulate the proposed maze applications, showing that this approach permits solving complex applications by implementing them...

In bacteria, programmed cell death is mediated through the unique genetic system called "addiction module," which consists of a pair of genes encoding a stable toxin and an unstable antitoxin. The mazEF system is known as an addiction module located on the Escherichia coli chromosome. MazF is a stable toxin, and MazE is a labile antitoxin interacting with MazF to form a complex. MazE and the Ma...