TALKESPORT

Cloud9’s performance at the IEM Katowice 2020 North America Closed Qualifier had been surprisingly good even though it was a debut performance with their new roster. The team had remained dominant throughout the upper brackets of the qualifiers and had even secured a map advantage for the best of five grand finals after besting Complexity in a best of three series.

The finals of the qualifiers had the upper bracket finalist Cloud9 clashing against the lower bracket finalist MIBR. The default map was scored in favor of Cloud9 in the best of five thanks to the map advantage that they had secured earlier. Having to drop the default map to Cloud9, the pressure on MIBR was intense to win the series for a chance at the IEM Katowice 2020 main event.

The first map that came into play was Train. The Terrorist side of MIBR took a half time lead of 8-7 even though train is a very Counter-Terrorist sided map. After half time and side change, the Brazilian defense traded rounds with the Americans offense but finally managed to come out on top with a 16-13 victory. The score was set 1-1, and the series moved on to the second map.

Overpass was the second map of the day. On their map of choice, the Cloud9 roster ran over MIBR’s CT side and took a massive lead of 12-3 in the first half. Comeback was a long gone dream for MIBR at that point of the game. The Americans maintained their control over the game even in the second half, losing only a single round to MIBR. In conclusion, Cloud9 took the map 16-4 and went 2-1 in the series.

The game went further into the third map which was Inferno. This was MIBR’s last stand and even though Cloud9 took the early rounds with dominating performances from its player, MIBR managed to go into the second half giving away only a single round advantage to Cloud9. The Brazilian front gave its best to secure the map by taking three round back to back after half time, but their efforts were cut loose by Cloud9 who came back into the game and took the map 16-12. Thus, Cloud9 took the series 3-1 against MIBR and managed to secure their spot at the IEM Katowice 2020 main event.

Now with the NA and Asia qualifier coming to its conclusion, we eagerly waiting to find out the teams which will make it through the EU and Oceania qualifiers and clash with the teams who have been invited or have qualified for the IEM Katowice 2020 showdown.

The current list of teams taking part in IEM Katowice 2020 are:

• Astralis
• mousesports
• fnatic
• Liquid
• Vitality
• Natus Vincere
• 100 Thieves
• Evil Geniuses
• NiP
• Virtus.Pro
• EU Qualifiers 1st slot: G2
• EU Qualifiers 2nd slot: FaZe
• Asia Qualifiers: ViCi
• North American Qualifiers: Cloud9
• EU Qualifiers 3rd Slot: TBD
• Oceania Qualifiers: TBD

The player models introduced in the Shattered Web update for CS:GO had faced a lot of love and hate reaction from the community. While most players were welcoming to the idea of using new character models in the game just like weapon cosmetics, many of the veterans who were used to the default models didn’t like the idea of adapting to the newer ones added into the game. Many players complained that it was hard to react to the greener player models on Cache which itself is a very green map, some also found it difficult to spot the player models on Mirage which were on the yellower side of the spectrum just like the map. The possibility of camouflage due to similar colour of player models and maps might seem pretty small, but players were already abusing this to gain a slight bit of advantage on certain maps like mentioned above. CSGO is a very competitive shooter and even the smallest of the advantage can cost you a match, the idea of using particular player models on certain maps to gain an advantage is simply against the idea of competitive gameplay and makes the game unfair.

After their introduction into the game, most of the 3rd party matchmaking clients like FACEIT didn’t waste much time in disabling the player models on their servers to promote the spirit of competitive gameplay. This move of FACEIT had earned a lot of praises from the community and was highly welcomed. Although, in a recent turn of events a Reddit user by the name of griizzylyyc found out that FACEIT has re-enabled players models on their Mythic hub. His investigations led him to contact one of the FACEIT admins of the hub who explained that the move came in light of VALVE forcing FACEIT to re-enable player models on their servers. The user has uploaded screenshots of his conversation with the admin where the admin can clearly be seen pointing out that this move of VALVE is only concerned with generating more revenue for them by pushing users to buy their players skins more.

The Shattered Web update has been a total blessing for the CS:GO community as this update finally brings an Operation into the game after years of stagnancy. We all got busy hunting for stars and completing the weekly missions when the update launched, but there was a small change we all might have ignored, that was the proficiency with which the bots attacked us in the exclusive Guardian missions. The bots surprisingly seemed very well-coordinated and even used smokes and flashbangs at times, similar to real human players and their behaviour.

The improvement in the CS:GO AI has been exponential ever since Valve announced that they will be improving the in-game AI in their September 2019 update. The update had introduced decision making for bots based on behaviour trees as an early framework which Valve hoped to improve on. The most notable change to the AI in CS:GO is possibly observed at random times in Valve Deathmatch when a bot can just one tap you from nowhere before you can even react or just land an impossible flick shot in your face. Each individual bot in CS:GO takes in information like sounds and sightings of the enemy and processes them to act on and carry out actions which are limited to their logic code. They even have their own form of memory (short term and long term retention capability although both lasts only for mere seconds). The bots most notably seem to prioritize objectives over most things as per their code. Currently, we can say that Valve has done a lot of work to make their bots imitate human-like aim, but what really impressed us is how they have designed the bots in Guardian Missions allowing them to even use utilities to their advantage just like humans play.

Sadly, the decision making of the Guardian AI isn’t fully self-learnt or automated as the developers have uploaded specific logic codes for each mission which explains why their executes although pretty good, were fairly predictable, to begin with. In the end, the behaviour tree-based decision making as implemented by Valve isn’t complex enough to fully automate the entire decision making of a bot like a neural network-based decision-making system, where almost the entire thought process of a bot is automated based on the information received and it becomes a self-learning process where the bot can come up with some really complex strategies which the players are totally not prepared for based on how the game is going. In the current state, the in-game AI is very limited in what it can do but it has come a long way in terms of improvement and growth.

Although there is much more to be wished for, it is still good to know that Valve is doing their best to improve their in-game AI and trying to implement more human-like features to the bots to make them even more competitive.