When Queen Samara Rani fulfills the promise she made to Emperor Valentin Kos to visit his court and meet with his advisors, she knows they won’t welcome her with open arms, especially when she’s been tasked with discovering the traitors within their ranks—traitors she tricked out of five million credits. As soon as Samara begins her investigation it becomes clear that Valentin’s advisors want her gone and they aren’t picky about how. After their tactics turn violent, Samara and Valentin race to unravel the web of treachery and lies before the next attack ends in tragedy. When the conflict escalates in ferocity and rumors start blaming Samara, she is forced to continue her hunt alone. Uncovering traitors is difficult when courtiers learn to lie before they learn to walk, and one misstep could cost her life. However, Rogue Queens aren’t easy to kill and Samara has more than a few tricks of her own.

When the Quint Confederacy and the Kos Empire went to war—again—Queen Samara wisely kept her Rogue Coalition out of the conflict. But staying neutral in a galactic war doesn’t pay the bills, not when both sides refuse to trade with neutral sectors.. With her people on the brink of starvation, Samara hatches a daring plan to snatch the kidnapped Kos Emperor from the Quint mercenaries holding him. The Kos Empire will pay a fortune for their emperor’s return, enough to feed the Coalition’s citizens while they wait for the return to a begrudging peace. But when her plan goes sideways, Samara finds herself evading Quint mercenaries with the very man she intends to capture. And the more time she spends with Valentin Kos, the more she realizes that he’s not the coldly indifferent villain she imagined. Torn between duty and desire, Samara must decide if saving her people is worth giving up the one thing she’s always wanted.

When Queen Samara Rani fulfills the promise she made to Emperor Valentin Kos to visit his court and meet with his advisors, she knows they won't welcome her with open arms, especially when she's been tasked with discovering the traitors within their ranks-traitors she tricked out of five million credits. As soon as Samara begins her investigation it becomes clear that Valentin's advisors want her gone and they aren't picky about how. After their tactics turn violent, Samara and Valentin race to unravel the web of treachery and lies before the next attack ends in tragedy. When the conflict escalates in ferocity and rumors start blaming Samara, she is forced to continue her hunt alone. Uncovering traitors is difficult when courtiers learn to lie before they learn to walk, and one misstep could cost her life. However, Rogue Queens aren't easy to kill and Samara has more than a few tricks of her own.

Queen Samara Rani knows she’s likely walking into a trap, but agreeing to meet with Commander Adams is the fastest way to get within striking distance of the Quint Confederacy’s biggest traitor and her sworn enemy. Adams attacked her home and destroyed her ship, and if he’s not stopped, he will ruin the tentative peace between the Kos Empire and the Quint Confederacy—and Samara’s chance at future with Emperor Valentin Kos. Samara is determined to serve up some well-deserved payback, but she is no longer a lone assassin, and despite her protests, her friends and allies refuse to let her undertake such a perilous mission without them. Even Valentin, usually the voice of reason, refuses to stay behind. Samara is loath to put her friends in danger, and taking a team carries its own risks, so she makes plans to keep them safe, no matter what the cost. When Adams threatens that safety, and everything she holds dear, Samara vows to show him exactly how she earned her deadly reputation—and why one should never cross the Rogue Queen.

Diece is the right hand man to the most powerful family in the Italian Mafia. He's ruthless, brutal, and has been tasked with protecting me after I stuck my neck out for his boss.That doesn't mean I trust him, though.Against my will, Diece whisks me away under the guise of keeping me safe, but I'm not about to exchange one prison for another. When he finds out what I've been through at the hands of my previous captor, he begs me to let my guard down. To let him in. But if I do, he'll find out the truth, and I can't let that happen. Not just for me, but for his safety too.He says he won't let anyone hurt me. He has no idea who I'm running from.*Contains sensitive subjects that may be offensive to readers. Intended for readers 18+

Grandmaster Damian Lemos presents a repertoire for White in the Queen’s Gambit, one of the most famous chess openings. The Queen’s Gambit enjoys a long and illustrious past. It has been played by virtually all the strongest grandmasters in the history of chess, and today it remains a popular choice for players of all levels. White’s opening moves in the Queen’s Gambit are built on sound strategic principles, and it can lead to positions rich in both tactical and positional play. It’s a perfect opening to use in order to develop your chess understanding. It’s a perfect opening to use in order to develop your chess understanding. There are many defences that Black can employ against the Queen’s Gambit and it’s easy to become confused by the countless options for both White and Black. Lemos tackles this problem by providing a concise, easy-to-learn and practical repertoire that is suitable for players of all levels. Using illustrative games, Lemos examines the typical tactics and strategies for both sides, and highlights the key move order issues. This book tells you everything you need to know about playing the Queen’s Gambit. * A complete repertoire with 1 d4 d5 2 c4 * Over 50 games with grandmaster analysis * Written by a Queen’s Gambit expert

Consider the problem of a robot (algorithm, learning mechanism) moving along the real line attempting to locate a particular point ? . To assist the me- anism, we assume that it can communicate with an Environment (“Oracle”) which guides it with information regarding the direction in which it should go. If the Environment is deterministic the problem is the “Deterministic Point - cation Problem” which has been studied rather thoroughly [1]. In its pioneering version [1] the problem was presented in the setting that the Environment could charge the robot a cost which was proportional to the distance it was from the point sought for. The question of having multiple communicating robots locate a point on the line has also been studied [1, 2]. In the stochastic version of this problem, we consider the scenario when the learning mechanism attempts to locate a point in an interval with stochastic (i. e. , possibly erroneous) instead of deterministic responses from the environment. Thus when it should really be moving to the “right” it may be advised to move to the “left” and vice versa. Apart from the problem being of importance in its own right, the stoch- tic pointlocationproblemalsohas potentialapplications insolvingoptimization problems. Inmanyoptimizationsolutions–forexampleinimageprocessing,p- tern recognition and neural computing [5, 9, 11, 12, 14, 16, 19], the algorithm worksits wayfromits currentsolutionto the optimalsolutionbasedoninfor- tion that it currentlyhas. A crucialquestionis oneof determining the parameter whichtheoptimizationalgorithmshoulduse.