Both Prey and Predator Features Determine Predation Risk and Survival of Schooling Prey

Predation is one of the main evolutionary drivers of social grouping. While it is well appreciated that predation risk is likely not shared equally among individuals within groups, its detailed quantification has remained difficult due to the speed of attacks and the highly-dynamic nature of collective prey response. Here, using high-resolution tracking of solitary predators (Northern pike) hunting schooling fish (golden shiners), we not only provide detailed insights into predator decision-making but show which key spatial and kinematic features of predator and prey influence individual's risk to be targeted and survive attacks. Pike tended to stealthily approach the largest groups, and were often already inside the school when launching their attack, making prey in this frontal "strike zone" the most vulnerable to be targeted. From the prey's perspective, those fish in central locations, but relatively far from, and less aligned with, neighbours, were most likely to be targeted. While the majority of attacks (70%) were successful, targeted individuals that did manage to avoid capture exhibited a higher maximum acceleration response just before the attack and were further away from the pike's head. Our results highlight the crucial interplay between predators' attack strategy and response of prey in determining predation risk in mobile animal groups.

Aksi Penyerangan Non-Player Character (NPC) Menggunakan Metode Naive Bayes pada Shooter Game

<p>Aksi penyerangan pada <em>non-player character </em>(NPC) merupakan salah satu substansi penting dalam pembuatan <em>game</em>. Dalam melakukan penyerangan diperlukan strategi khusus agar NPC tidak mudah dikalahkan. Salah satunya adalah adanya variasi serangan terhadap pemain. Salah satu metode yang digunakan untuk mengatur penyerangan NPC adalah <em>rulebase</em>. Metode <em>rulebase </em>dapat memberikan variasi serangan sesuai kondisi NPC, namun metode <em>rulebase </em>bisanya menghasilkan <em>behaviour </em>yang statis dan tidak adaptif jika terdapat kondisi baru. AI seperti ini akan mudah diprediksi dan repetitif sehingga menurunkan tingkat tantangan bermain <em>game</em>. Untuk mengatasi masalah tersebut banyak peneliti yang menggunakan teknik <em>learning</em>. Salah satunya menggunakan metode <em>naïve bayes.</em> Pada penelitian ini dilakukan penerapan metode <em>naïve bayes </em>sebagai strategi penyerangan NPC pada <em>shooter game</em>. Metode <em>naïve bayes </em>digunakan untuk keputusan serangan yang diambil oleh NPC. Adapun parameter yang digunakan untuk keputusan penyerangan adalah nyawa, jarak, jumlah granat, dan jumlah amunisi yang dimiliki NPC. Sedangkan keputusan penyerangan dibagi menjadi serangan tembak, serangan granat, dan serangan pisau. Hasil penelitian menunjukkan penerapan metode <em>naïve bayes </em>membuat NPC mampu melakukan penyerangan secara otonom jika terdapat kondisi baru dengan akurasi 80%. Penerapan metode <em>naïve bayes </em>juga lebih unggul dalam persentase kemenangan NPC dibanding metode <em>rulebase</em>. Tingkat kemenangan NPC menggunakan metode <em>naïve bayes </em>sebesar 60% sedangkan <em>rulebase </em>sebesar 16%.</p><p> </p><p><em><strong>Abstract</strong></em></p><p><em>Non-Player Character’s (NPC) attacks behaviour is one important substance in making games. While NPC attacks needs specific strategy to not get defeated easily. One of the NPC attacks strategy is a variation of offense to player. One of the methods to manage the NPC attack strategy is rulebase. Rulebase method can give variations of the NPC attacks according in conditions, but rulebase method usually producing static behaviour and not adaptive where there is new condition. AI like this would easy too predictive and repetitive so that decrease the challenge of playing games. To overcome these problems, we use naïve bayes method. In this study, naïve bayes method are applied as an NPC’s attack strategy to the shooter game. Naïve bayes method used for attack decisions taken by the NPC. The parameters used for the attack’s decision are health point, distance, number of grenades, and number of ammunitions owned by the NPC. While attacks decision is divided into firing attacks, grenade attacks, and melee attacks. The results showed that the use naïve bayes method can attack autonomously if there are new condition with an accuracy of 80%. The implementation of naïve bayes method at NPC more superior than rulebase method in percentage of NPC winning. The NPC win rate uses the naïve bayes method is 60% while the rulebase is 16%.</em><em></em></p><p><em><strong><br /></strong></em></p>

New Betweenness Centrality Node Attack Strategies for Real-World Complex Weighted Networks

In this work, we introduce a new node attack strategy removing nodes with the highest conditional weighted betweenness centrality (CondWBet), which combines the weighted structure of the network and the node’s conditional betweenness. We compare its efficacy with well-known attack strategies from literature over five real-world complex weighted networks. We use the network weighted efficiency (WEFF) like a measure encompassing the weighted structure of the network, in addition to the commonly used binary-topological measure, i.e., the largest connected cluster (LCC). We find that if the measure is WEFF, the CondWBet strategy is the best to decrease WEFF in 3 out of 5 cases. Further, CondWBet is the most effective strategy to reduce WEFF at the beginning of the removal process, whereas the Strength that removes nodes with the highest sum of the link weights first shows the highest efficacy in the final phase of the removal process when the network is broken into many small clusters. These last outcomes would suggest that a better attacking in weighted networks strategy could be a combination of the CondWBet and Strength strategies.

The attack strategy for a quantum key distribution protocol based on Bell’s theorem

A new eavesdropping strategy is proposed for the Quantum Key Distribution (QKD) protocol. This scheme represents a new kind of intercept/resend strategy based on Bell’s theorem. Quantum key distribution (QKD) provides the foremost reliable form of secure key exchange, using only the input-output statistics of the devices to realize information-theoretic security. In this paper, we present an improved QKD protocol that can simultaneously distribute the quantum secret key. We are already using the QKD protocol with simulated results matched completely with the theoretical concepts.